Student enthusiasm for, and success in, the mathematical sciences begins with the recruitment of a diverse faculty committed to excellent teaching, active engagement through broadly defined scholarship, and service to their institution and larger mathematical community. Such faculty should be engaged and supported in their professional development and evaluated in a transparent and equitable manner.

This statement is guided by the original Guideline Statement #1, written in 2017, but updated to reflect the MAA’s focus on justice, equity, diversity, and inclusion as well as increased attention to the importance of having a supportive department culture.² We describe best practices in terms of recruitment, development, and evaluation of faculty members and believe that if these best practices are put into practice, then faculty members are more likely to be retained. MAA members come from a wide variety of academic institutions with different foci, curricula, and governing regulations, thus not all faculties and departments can implement every best practice but this document will provide food for thought.

As was written in Statement #6, “the MAA recognizes that Black, Indigenous, and Latinx/Hispanic people, women, and individuals who have disabilities have been historically excluded from mathematics in the United States and as such are vastly underrepresented in the field. In this statement, we will use the terms “underrepresented” and “underserved” to refer to faculty from the aforementioned groups.” We also use the term “department” as a catch-all term when “program” or “division” might be used at an individual institution.

1. Types of Faculty Positions

There are varying types of faculty positions and titles for those positions, ranging from adjuncts who teach just one course, to tenured professors at the highest rank. Some faculty are employed for just one semester, others for decades, but all deserve to be members of a well-functioning department that encourages and supports active professional development. Much of what follows applies to entire departments and their wide range of faculty members, while some will be more pertinent to those who are required to go through some form of formal evaluation (e.g. tenure).

In most mathematical sciences departments, the majority of advanced courses should be taught by faculty members who have disciplinary expertise and bring continuity, a sense of community, and institutional knowledge to a program. According to the 2015 CBMS survey, roughly 70% of advanced-level mathematics courses were taught by tenured or tenure-eligible (TTE) faculty, the majority of whom are full-time.

As institutions face financial strain, the hiring of non-TTE faculty has become more common. The 2015 CBMS survey shows that in calculus-level courses, the use of TTE faculty declined by 15% since the 2010 survey, while the use of non-TTE faculty increased by 48%. The reality is that non-TTE faculty are so vital to most institutions that their well-being and professional development must be carefully considered.

2. Recruitment

The mathematical sciences are in constant need of being strengthened by individuals from the broadest possible pool of talent. This is best accomplished when those teaching mathematics are drawn from a diverse pool and are committed to supporting students of all backgrounds.

Recruiting strategies may differ depending on the type of open faculty position, but in all cases it is critical to have a transparent, deliberative process that seeks to recognize and redress biases. Special efforts should be made to recruit and hire members of underrepresented groups. Human resources departments and DEI (Diversity, Equity, and Inclusion) officers should be consulted when available, and committees must familiarize themselves with institutional policies around hiring practices.

The following best practices for the hiring process are adapted from an MAA Focus article [A].

• Determine departmental priorities. Before conducting a search, members of the department should determine what their priorities are. Will the search be for the best possible scholar in a particular field, an experienced and effective teacher, a skilled practitioner of high impact practices, a leader in DEI initiatives, or something else?
• Form a search committee. Every application should be read by at least two people to help prevent conscious or unconscious bias. Hiring an adjunct who will teach just one course probably only requires a committee of two, but hiring a tenure-track faculty member will need a bigger commitment even if that necessitates having committee members from outside of the department.
• Establish decision-making processes. Before any applications are read, the search committee should establish protocols for evaluating applicants, and for making decisions or recommendations about hiring.
• Advertise and engage widely to get a diverse pool of candidates. Mathjobs.org continues to be of primary importance, but potential applicants get information from the National Association of Mathematicians, Association for Women in Mathematics, Society for Advancement of Chicanos & Native Americans in Science, Lathisms, Mathematically Gifted and Black, TODOS, and Math Alliance.
• Interrupt biases. Positive and negative biases can enter the recruitment and hiring process at any stage, both consciously and unconsciously. Committee members should regularly take part in equity training, reflect on what biases they might have, and assess how they might be giving an advantage to some applicants over others. It is crucial to follow the established protocols and rubrics so that committee members focus their attention on agreed upon priorities and desired qualifications.
• Negotiate equitably. It is widely reported that men negotiate for higher salaries and better starting packages than women, and white people negotiate for more than people of color (see [He], [K], [B]). However, some research shows that when women are explicitly told that wages are negotiable, differences with men disappear [Le]. Thus, to combat inequity in negotiations we recommend being forthright with all candidates about what people in similar positions have both successfully and unsuccessfully negotiated in the past. Additionally, most institutions have data on average salaries in comparison to their peer institutions; this data can be helpful for job applicants at every stage of the process.

3. Faculty Development

Mathematics departments should proactively provide all faculty with robust opportunities for professional development in teaching, scholarship, and service. Department members–with tenured faculty taking the lead–are responsible for creating an atmosphere where professional growth and innovation are encouraged and celebrated. As faculty have diverse needs and may therefore face different barriers to pursuing growth, departments should broadly and creatively consider the forms that support might take, including financial compensation, time (in the form of course release), and mentorship. Whenever possible, appointments of non-TTE faculty should be for at least two years to give individuals adequate time to develop their scholarship, teaching, and other aspects of their career before having to apply for jobs again. Mentoring junior faculty–both formally and informally–should be seen as the work of the entire department. Particular attention must be given to the development of faculty from underrepresented groups.

The categories of teaching, scholarship, and service not only intersect, but are defined differently at individual institutions. The best practices below can be adjusted to fit varied situations.

1. Teaching
   In documents concerning teaching practices (including Guideline Statement #3 and Guideline Statement #4), quality teaching is often described as a complex endeavor requiring considerable expertise. Faculty must be equipped to implement a variety of research-informed pedagogical practices that promote deep mathematical thinking in an equitable and inclusive environment while addressing students’ unique needs.

• Courses assigned to early-career faculty should be selected with their input and chosen in such a way as to support their pedagogical development and eliminate undue burden. New faculty should be limited to at most two preparations per term during their first few semesters, when possible.
• In order to best serve diverse learners, faculty should be encouraged to experiment with a variety of research-informed pedagogical techniques in the classroom without fear of repercussions. Departments might encourage faculty to document the results of their efforts and share their experiences to promote a culture of pedagogical innovation and continuous improvement.
• Department members should be available to observe one or more class periods if a colleague would like informal feedback about their pedagogical practices and innovations. Using established rubrics can help guide productive conversations.
• Department leaders should establish regular conversations about pedagogy to communicate the value of teaching to all department members. Junior and senior faculty members can help each other stay current with new developments in teaching and find joy in their work.
• Departments and universities should provide all faculty with ongoing structured opportunities to further develop pedagogical expertise.
• When possible, financial support should be made available, and the process for obtaining it transparent, for new faculty to attend intensive programs (e.g. Project NExT, MAA webinars, mini-courses, etc.) designed to support the launch of their career.
• Departments should provide graduate assistants with substantial training prior to teaching, ongoing formative monitoring of their classroom work, and opportunities to develop their philosophy of teaching and pedagogical knowledge.
• Faculty members should employ accessibility standards and use support resources on campus (e.g. advising centers, teaching centers).

2. Scholarship

• Departments should help all faculty, especially junior faculty and those from underrepresented groups, to identify internal and external funding sources to support research, travel to conferences, grant-writing, and other scholarly activities.
• Departments should be aware of additional challenges faced by caregivers that make scholarly travel difficult, undesirable, or impossible. To the extent possible, departments may ameliorate some of these issues by, for example, valuing participation in virtual conferences or financially supporting child care while attending conferences.
• The department should work to ensure that library holdings, journal subscriptions, and technology are adequate to meet the research needs of its faculty.
• Course releases can provide early-career faculty with the time and freedom to initiate and develop their research program. Sabbaticals at regular intervals are important for helping faculty members enhance their teaching and scholarly interests.
• Department chairs and senior faculty should learn about junior faculty members’ research and be intentional about helping them make connections to colleagues doing relevant work and expand their professional network.
• Senior faculty could invite new faculty to collaborate on research, publications, grant-writing, or presentations to scaffold their scholarly development.
• Departments should invite VITAL (Visitors, Instructors, Teaching assistants, Adjuncts, and Lecturers) faculty members to openly discuss their career plans with the intent of providing appropriate support and mentorship. VITAL faculty who seek a permanent tenure-track position might benefit from teaching development and/or opportunities to work on scholarly activity and service, based on their long-term career goals. They should be invited to relevant professional opportunities at the institution.

3. Service

• Senior faculty should share some of the experiences they have had with service on campus (at the department, college, and university levels) as well as externally so that new faculty quickly become aware of the variety of service opportunities–such as refereeing and reviewing, organizing sessions at conferences, serving on committees through professional societies, and collaborating to host regional and national conferences–and the extent to which they should serve.
• Conversations with a department leader or trusted mentor will help new faculty envision where they might contribute to their institutional and professional communities, possibly leading to nominations for elected committees.
• Expectations for faculty service as academic advisors varies between institutions, including whether academic advising even falls within faculty purview. Universities should provide development opportunities to faculty with advising responsibilities, and those who attend should be lauded. Experienced faculty should proactively share helpful advising materials and offer mentorship to faculty who are new to advising responsibilities.

4. Evaluation

All faculty members, whether full- or part-time, TTE or not, stand to benefit from having regular conversations with their peers about the nature of their professions. For most faculty members, this means discussing teaching, reflecting on scholarship, and articulating service to the institution and to the profession. Often, these conversations are formalized in evaluations of non-TTE faculty, formative pre-tenure reviews for tenure-track faculty, and summative evaluations of tenure dossiers. However, revisiting the areas of teaching, scholarship, and service should be done on a regular basis for all faculty, even outside of these formal periods of review. Such conversations are for the purpose of assistance via formative feedback and can center on the aspects of the job that are the most important, most difficult, or most in development for the faculty member. They also serve as a method of building a culture of transparency and respect, which can help with the overall climate of the department.

Ultimately, formative evaluation should be about growing professionally. Thus, ways in which the informal conversations surrounding one’s academic position can occur are rooted in the professional development ideas detailed above. For example, inviting a colleague to observe your class and having a conversation about it afterward or having a lunch meeting with colleagues to talk about teaching methods are informal formative teaching feedback methods. Discussing professional goals with your colleagues or sharing scholarship success and difficulties are formative ways to gather evaluation about scholarship and service.

The following recommendations are primarily for when a formal review takes place:

• For transparency, the department and institution should clearly communicate in writing the expectations for performance to the faculty member upon hire. Expectations should be continually articulated to junior faculty and VITAL faculty by experienced faculty mentors and department chairs.
• Whenever feedback about a faculty member’s performance is given, it should be delivered in a constructive way, cultivating improvement and alignment with the mission and goals of the department and institution. Feedback is most useful when given by someone familiar with the work of the faculty member. For a formal review, such as a pre-tenure review or tenure decision, feedback should be given in writing and the faculty member should be given a chance to respond to the feedback.
• Faculty members should not be reviewed or evaluated on elements that were not articulated as part of their contract. For example, part-time faculty who are not expected to perform institutional service should not be evaluated on such.
• When seeking a letter of recommendation from someone outside of the faculty member’s institution, the person requesting the letter should be clear about what is expected in the letter. In particular, if there is a facet of the individual’s portfolio that the letter should focus on, or if there are particular values or traits that should be discussed, these should be communicated to the letter writer.

Teaching

• Excellence in teaching can be demonstrated in many ways, for example including developing high quality curricula or teaching materials, teaching using student-centered methods, sample student work, presentations at conferences, and professional development [Re]. See also Guideline Statement #4 and #6.
• While some consideration can be placed on student course evaluation data, the responses themselves should only be a small part of the evaluation of a faculty member’s teaching due to known biases introduced by such instruments [C]. Instead, more weight should be placed on how a faculty member responds to student feedback.
• Faculty members should be encouraged to try pedagogical approaches which are new to them and not be penalized if those approaches need improvement after the first time they are implemented. Clear communication between faculty members and those doing the evaluation can help in such a situation.
• Another way to gain direct evidence of teaching excellence is through observation. Each teaching faculty member is encouraged to be observed in the classroom (or online, if teaching virtually) at least once per academic year by someone with an interest in helping the faculty member become a better teacher. This can be a colleague in the mathematical sciences, a professional in a center for teaching and learning, or other appropriate individual. After the observation, a discussion between the faculty member and the observer should take place about positive aspects and areas for improvement [Fl].
• Faculty members should document their efforts to develop their pedagogy such as attending teaching workshops, conferences, and training programs.

Scholarship

• Scholarship in the mathematical sciences has no universal definition. Rather, the circumstances surrounding the expertise of the faculty member, the ways in which they can make a contribution to the mathematical community, the institutional context, the mission and goals of the department, and many other factors play a role in determining how scholarship should be evaluated. In light of this, departments are encouraged to embrace a wide range of scholarly activities as they align with the needs of the department, institution, and mathematical community [J]. Besides publications in peer-reviewed mathematical journals, examples of ways that faculty members can demonstrate scholarship in their area include research on mathematics teaching and learning, synthesis of existing scholarship, collaboration with the K-12 community, developing standards for content and teaching, expository writing, and development of curricula [Re].
• To build a culture of transparency, expectations surrounding scholarship should be clearly communicated upon hire. Continuing feedback about scholarly activity is important for faculty, especially junior faculty.
• Tenure-track faculty should be given annual feedback on their performance relative to scholarly production (if scholarship is expected).
• Faculty members whose scholarly activity is not congruent with the expectations of the department or institution should be informed of this long before any punitive action occurs. Scholarship is a process that takes time to develop and even longer if to be reviewed by peers. It is unreasonable to expect a faculty member to pivot their scholarship in a short period of time.

Service

• Faculty members should consult with their chair or appropriate figure to discuss what types of service will promote professional growth and engagement which is congruent to the mission and needs of the department and institution.
• It is the responsibility of the faculty member to accurately convey the type and magnitude of their service to those who are in a position to evaluate them. For instance, those serving on national committees should detail the amount of time such an assignment takes and the work involved.

5. Concluding remarks

Given the aforementioned best practices for recruitment, professional development, and evaluation, we emphasize that faculty satisfaction is highly related to their experiences of collegiality from department colleagues (see [D], [Ha], [Ro]). Generally, a workplace climate “affects employee recruitment, adjustment, productivity, stress, and commitment” [Li]. Since there has been a great focus on campus climates that tend to student, faculty, and staff needs, mathematics departments should inquire into their existing department climate using climate surveys that are widely available online. While there is no simple way to define department climate, the following definition for a department climate can be adopted: “The atmosphere or ambiance of an organization as perceived by its members. An organization’s climate is reflected in its structures, policies, and practices; the demographics of its membership; the attitude and values of its members and leaders; and the quality of personal interactions” [Fi]. Research indicates the important role that department climate plays on faculty success, satisfaction, engagement and retention (see [Ro], [S]) and we encourage mathematics departments to explore some major principles that impact faculty members’ lived experiences. These principles include, but are not limited to: transparency, equitable support, respect, accessibility, inclusivity, belonging, and community building in general [Fi]. As these principles affect faculty retention, professional development, and evaluation, it is recommended that departments perform regular audits of their climate to gauge how their faculty members experience the intellectual, social, emotional, and physical environments in the department.. Notes

1. This is a revision of the original Statement 1 approved by MAA in September 2017. Written by the following members of CFD: Edward Aboufadel, Connie M. Campbell, Minerva Cordero, Timothy Flowers, Debra Lynn Hydorn, Tyler J. Jarvis, Herbert E. Kasube, Perla L. Myers, Benedict K. Nmah, Emily E. Puckette, and Jennifer Quinn.
2. Best Practices statements are the descendents of the 1993 Guidelines for Programs and Departments in Undergraduate Mathematical Sciences, published by the MAA. Some of the language in the current statement is borrowed from the 1993 document, its 2003 revision, or original best practices statements.

6. References

Bonous-Hammarth. The Black Academic: Faculty Status among African Americans in U.S. Higher Education. The Journal of Negro Education, vol. 69, no. 1/2, 2000, pp. 112–27. JSTOR, http://www.jstor.org/stable/2696268. Accessed 9 Jan. 2023.

Mathematical sciences departments should prepare students to use mathematics in a modern technological environment. As noted in the 2015  CUPM Curriculum Guide [16]:

Employers want graduates to have experience with technology, be it programming or using software applications. Using an appropriate tool to solve a problem is a universally-valued skill. Effective communication of ideas often requires technology for images, data representations, and notation. Most important, for professional and personal needs, students need the ability to learn to use emerging technologies. We therefore have a responsibility to encourage and enable our students to learn technologies alongside their mathematics.

To achieve this objective, faculty, departments, and institutions should collaborate to ensure that essential resources are available for faculty and students. Additionally, faculty and administrators should work together to develop appropriate solutions for their institutions. Many problems can, and will, arise as students, faculty, and departments adapt to the changing roles of technology in research, education, and applications.

A) All faculty should be provided with the basic resources necessary for them to perform the teaching and the scholarly activities they were hired to do. These include the following:

i) Sufficient office space.

ii) Well-lit classrooms with adequate board space and projection facilities.

iii) Library holdings and subscriptions necessary for the development of teaching and scholarship.

iv) Computing resources necessary for teaching and scholarship. [12]

v) Staff support, including administrative assistance and computing support.

vi) Professional development funds and resources.

New faculty should have access to these resources when they begin work in a faculty position.

B) All students should have access to all the basic resources required for learning the mathematical sciences and preparing for their future careers.  These include the following:

i) Computing resources necessary for their work.

ii) Study space, including shared or common space near faculty.

iii) Space for faculty consultation.

iv) Basic academic support outside the classroom.

v) Library resources sufficient to support student learning and provide enrichment materials for undergraduate student support.

In addition, university administrators should ensure that appropriate and legally required accommodations, such as adaptive technology, are made for any faculty, staff, or students with documented disabilities.

Details about the required resources are given below.

i) Office Space: All full-time faculty members should have private offices. Each part-time faculty member should have a desk and office space that allows confidential conferences with students outside the classroom. Where possible, faculty offices should be located near other faculty with common research or teaching interests to facilitate collaboration. [11]

ii) Classrooms: Classrooms should be safe, clean, well lit, and equipped with adequate board space and computer projection equipment and screens.  This includes enough whiteboard or chalkboard space to allow instructors to write out all the details of a typical proof or argument without erasing and in a large enough hand that students can read it easily.  Many classrooms designed for teaching nonmathematical subjects do not have sufficient board space for mathematical instruction.   Where possible, classroom design should emphasize flexibility, with the potential for reconfiguration to adapt to a variety of teaching styles and methods.  The SCALE-UP classroom design model from North Carolina State University is a good example:  “The class spaces included a laptop computer with access to the Internet, 7-foot-diameter round tables, computer projection screens at opposite ends of the room, and large whiteboards covering the walls.” [15]  The Learning Spaces Collaboratory also has advice on classroom design.

iii) Library:

a. Library holdings and subscriptions should be sufficient to meet the scholarly needs of the program faculty. They should also provide resources for helping faculty improve their teaching.  Departments can review the MAA’s Basic Library List for suggestions.  If specific library materials are not available on site, they should be readily available electronically or through a process such as interlibrary loan.

b. Libraries should be staffed, scheduled, and located in such a way that their mathematical sciences holdings are readily available to all faculty members and students.

c. Library holdings and subscriptions should be reviewed regularly by a committee that includes representation from the mathematical sciences.

iv) Computing: Faculty should have access to all the computing resources they need to perform their jobs, including the following:

a. Up-to-date hardware and software.

b. Fast internet access.

c. All necessary data sets, and storage for very large data sets, as needed.  This is discussed in a recent report by the National Academies of Sciences, Engineering, and Medicine:  “It is precisely in the realm of moving from raw data via analysis to knowledge that the mathematical sciences are essential. Large, complex data sets and data streams play a significant role in stimulating new research applications across the mathematical sciences, and mathematical science advances are necessary to exploit the value in these data.” [13]

d. Training and time to learn to use new tools.

e. Well-trained computing support staff.  Computing support staff should be able to maintain the primary mathematical and instructional software packages used by the faculty and students.

These resources can have a profound impact on the teaching and learning of mathematics.  As noted in the MAA’s Instructional Practices Guide, “In today’s world, technology is ubiquitous and applicable to many aspects of instructional practice. As such, instructors should continually examine how and where technology fits into their work.” [11] Departments should regularly examine their investments in computing resources to ensure that needs are being met.

v) Staff Support: Faculty should have access to basic staff support, including department administrative assistance (secretarial support), computing support, and tutoring center support staff. Faculty should not be used as support staff unless it is a documented expectation of their employment, they are given a corresponding reduction in other duties, and their work on these assignments is recognized for tenure and promotion decisions.

vi) Professional Development Funds and Resources: Professional development is essential to faculty success. All full-time faculty members should have access to the resources necessary to participate in appropriate professional development.  As the National Research Council concludes, “The use of learning technology in itself does not improve learning outcomes. Rather, how technology is used matters more.” [13] Without support and training, incorporation of new technology may not actually be beneficial.

a. Faculty should receive funding to attend at least one professional conference each year.

b. Where possible, the institution should pay the membership dues for each full-time faculty member to join at least one of the mathematical sciences professional societies (e.g., MAA, SIAM, AWM, NAM, AMS, ASA, AWC, ACM).

c. Faculty who are expected to do scholarship should be given a sabbatical or research leave at appropriate intervals.

d. Faculty should receive support for course development, incorporating new technology into their courses, and for other major pedagogical changes to their courses.  This includes teaching load reductions for significant course development and training for new technology and new pedagogical methods. [5, 7, 9]

i) Computing:

a. For courses that use online homework or require use of specialized software, students should have ready access to a computing lab or other resources to allow them to complete their assignments, especially if they do not have their own computer or their own copy of the required software packages.

b. The National Research Council observes that “Computation is central to the future of the mathematical sciences, and to future training in the mathematical sciences . . . [I]t is apparent that an ability to work with data and computers is a common need . . . and indeed students with this training will be much more employable in those areas.” [14] Thus, students should have access to the most important computational tools and methods of the discipline.  Students majoring in the mathematical sciences should learn to use the standard software tools and computing languages used in business, industry, and government within their disciplines.  This should include at least one general purpose computer programming language and at least one of the industry-standard tools for numerical computing (see the appendix for details). [13, 16, 18]  Note: Popular software tools include many that are free or open source; accessing these tools need not represent a significant expense to the school, but it requires the institution to provide computer support staff (see items c and d, below).

c. Faculty who interact with students should know how to use the relevant software and computing languages. [7, 8, 11]

d. Computing support staff should be available to ensure that all the necessary classroom and lab machines are properly configured, and that software is properly installed and maintained. Students should be taught how to access the resources they need, whether the access is local or remote. Particular care should be given for instructions on accessing any remote resources available to students both within labs and for home and personal computers. Access instruction may come from faculty or support staff depending on an institution’s organizational structure.

e. Handheld calculators, including programmable graphing calculators, are not a suitable replacement for modern mathematical and computational tools.  Nevertheless, graphing calculators still play a significant role in many secondary school mathematics curricula, so departments should teach prospective secondary school teachers how to use calculators appropriately. [7]

ii) Study Space:

a. All students should have quiet space available to study and do homework.

b. Mathematical science majors should have a dedicated common study area where they can collaborate and study together.  This area should be located near faculty offices to allow opportunity for frequent contact between students and faculty.

c. When designing new or remodeled space for mathematical sciences departments and students, institutions should consult with both faculty and students about how to best use the space to maximize student learning. [15]

iii) Faculty Consultation: Faculty should have well-publicized, regular, and frequent office hours, and faculty offices should be easily accessible to students, and faculty. [11]

iv) Tutoring Support: Students in lower-division mathematical sciences classes should have access to basic tutoring support outside the classroom, allowing them to get help at times that faculty are not available.  This is commonly done in a tutoring center, staffed primarily by graduate students or advanced undergraduate students.  Tutors should be familiar with the software and other technology being used in the classes for which they are tutoring.

v) Library: Library holdings should be sufficient to support student learning and provide enrichment materials for student projects.

a. Holdings should include the publications labeled Essential, Highly Recommended, or Recommended, on the MAA’s Basic Library List for undergraduate mathematics.

b. Holdings should include enough advanced materials to support students in mentored research.

c. Libraries should be staffed and scheduled, and have materials located in such a way (locally or electronically) that their mathematical sciences holdings are readily available to the mathematical sciences faculty and their students.

… because computation is often the means by which methods from the mathematical sciences are applied in other disciplines and is also the driver of many new applications of the mathematical sciences, it is important that most mathematical scientists have a basic understanding of scientific computing. [13]

— the National Academies of Sciences, Engineering, and Medicine

SIAM’s Math in Industry resource states, “In this study we also took a closer look at the technical skills that graduates need, which tend to fall into three overlapping domains: mathematics, computation, and specific application domains . . . Computational skills include, at a minimum, experience in programming in one or more languages.” [18]   So, it is important for students to learn a general-purpose programing language as well as some standard numerical computing tools.  In certain cases, the tools may be part of the general programming language (e.g., NumPy and SciPy in Python), but this is not essential. We recommend that the choice of which tools and languages to teach students be dictated by what is commonly used in industry, business, and government for mathematical computation. [13, 16, 18]  At the time of this writing (2018), these include the following:

a. For statistics, R, Python, or SAS. (See https://www.r-project.org/ for R, and https://www.python.org/ for Python.) [2]

b. For mathematics, Python, (including NumPy and SciPy), MatLab, or Octave.

c. Note that Maple and Mathematica also have some numerical tools, but are not widely used in industry.  Nevertheless, with careful thought and work, those could be used to teach students the necessary numerical computing principles.

d. Sage/CoCalc is similar to Maple and Mathematica, but also allows the use of Python and R code.  (See https://cocalc.com/)

e. Julia is not yet in wide use, but it appears to be rising in popularity and is potentially very powerful. (See https://julialang.org/)

f. For data science, either Python or R, as well as SQL. This should also include standard tools and packages for data manipulation, such as Pandas or tidyr, and standard tools for machine learning, such as scikit-learn and TensorFlow. [3, 4, 6, 14, 19]  “Python and R are both widely used by data scientists, often in tandem, since they have different strengths and weaknesses.” [12]

a. Python.

b. C or  C++.

c. Possibly Java.  Although Java is a very popular language, it does not seem to be used as much as Python or C/C++ in mathematical applications.  Also, it appears to be declining in overall popularity, especially in mathematical settings.

Many popular programming languages are in wide use for non-mathematical applications but are not commonly used for mathematical computation. Therefore, these languages should not be the primary language for mathematical sciences students. These include languages such as Javascript, PHP, Perl, and Ruby.  Also, many popular languages are platform specific, including C#, Swift, Objective-C, and Visual Basic.  Unless it is known in advance that students’ careers will be primarily focused on programing for those platforms, these should not be the primary programming language for mathematical sciences students.

Many of the mathematical tools listed above are powerful tools for their specific application, but are too specialized to be considered general-purpose, full-scale programming languages. These include R, MatLab, Octave, Maple, SAS, and Mathematica. Typical teaching practice with these languages, such as simple use for plotting or calling pre-built functions, does not include functions, control flow, etc.  Therefore, learning these alone will generally not provide sufficient programming skill for typical students. Only if these languages are taught explicitly as a programming language with functions writing, control flow, debugging, commenting, recursion, I/O, data types, exception handling, etc, could they be sufficient.  In addition, students should be able to write working programs consisting of more than a hundred lines of code.  The following concerning statistics students also applies to mathematics students:  “It is no longer adequate training for statistics students to be able to analyze data using graphical user interfaces or to write simple scripts that do not use modular approaches (including writing functions and code using control flow) to process data.” [10]

[1] ACM Joint Task Force 2013. Computer science curricula 2013: Curriculum guidelines for undergraduate degree programs in computer science. Technical report, Association for Computing Machinery (ACM) IEEE Computer Society.

[2] American Statistical Association 2014. Curriculum guidelines for undergraduate programs in statistical science. Retrieved from http://www.amstat.org/education/curriculumguidelines.cfm. (2014).

[3] Anderson, P. et al. 2014. An Undergraduate Degree in Data Science: Curriculum and a Decade of Implementation Experience. Proceedings of the 45th ACM Technical Symposium on Computer Science Education (New York, NY, USA, 2014), 145–150.

[4] Anderson, P. et al. 2014. Data Science As an Undergraduate Degree. Proceedings of the 45th ACM Technical Symposium on Computer Science Education (New York, NY, USA, 2014), 705–706.

[5] Bottino, R.M. and Chiappini, G. 2014. Using Activity Theory to study the relationship between technology and the learning environment in the arithmetic domain. Handbook of International Research in Mathematics Education. Routledge.

[6] Cassel, B. and Topi, H. 2015. Strengthening data science education through collaboration. Workshop on Data Science Education Workshop Report (2015), 27–2016.

[7] Drijvers, P. 2015. Digital technology in mathematics education: Why it works (or doesn’t). (2015), 135–151.

[8] Drijvers, P. et al. 2010. Integrating Technology into Mathematics Education: Theoretical Perspectives. Mathematics Education and Technology-Rethinking the Terrain. C. Hoyles and J.-B. Lagrange, eds. Springer US. 89–132.

[9] English, L. 2009. Setting an agenda for international research in mathematics education. Handbook of international research in mathematics education. (2009), 3–19.

[10] Hardin, J. et al. 2015. Data Science in Statistics Curricula: Preparing Students to “Think with Data.” The American Statistician. 69, 4 (Oct. 2015), 343–353.

[11] Instructional Practices Guide | Mathematical Association of America. Accessed: 2018-03-16.

[12] Jarvis, D.H. et al. 2014. Computer Algebra System (CAS) Usage and Sustainability in University Mathematics Instruction: Findings from an International Study. Electronic Journal of Mathematics & Technology. 8, 4 (2014).

[13] National Academies of Sciences, Engineering, and Medicine 2013. The Mathematical Sciences in 2025. 

[14] National Academies of Sciences, Engineering, and Medicine 2017. Envisioning the Data Science Discipline: The Undergraduate Perspective: Interim Report.

[15] Park, E.L. and Choi, B.K. 2014. Transformation of classroom spaces: traditional versus active learning classroom in colleges. Higher Education. 68, 5 (Nov. 2014), 749–771. DOI:https://doi.org/10.1007/s10734-014-9742-0.

[16] Schumacher, C., Siegel, M., et al.. 2015. 2015 CUPM curriculum guide to majors in the mathematical sciences.

[17] Singer, S.R. et al. 2012. Discipline-based education research: Understanding and improving learning in undergraduate science and engineering. National Academies Press.

[18] Society for Industrial and Applied Mathematics 2012. Mathematics in Industry. Retrieved from https://www.siam.org/Publications/Reports/Detail/Mathematics-in-Industry. (2012).

[19] Veaux, R.D.D. et al. 2017. Curriculum Guidelines for Undergraduate Programs in Data Science.  Annual Review of Statistics and Its Application. 4, 1 (2017), 15–30. DOI: https://doi.org/10.1146/annurev-statistics-060116-053930.

Edward Aboufadel (CFD chair), Grand Valley State University
Connie Campbell, Gulf Coast State College
Timothy Flowers, Indiana University of Pennsylvania
Debra Lynn Hydorn, University of Mary Washington
Tyler J Jarvis, Brigham Young University
Gavin LaRose, University of Michigan
M. Leigh Lunsford, Longwood University
Audrey Malagon, Virginia Wesleyan University
Benedict K Nmah, Morehouse College
Emily E Puckette, University of the South
Karl Schmitt, Valparaiso University

October 2018

Faculty and departments should create policies and practices that support student success and encourage the inclusion of students from underrepresented groups in the field. In 2017, the MAA published its high-quality Instructional Practices Guide, providing “evidence-based instructional practices in undergraduate mathematics. Among the messages in the Guide is that efforts often begin with responsibly placing students in introductory courses, providing academic and advising support, and building a culture of inclusion that addresses matters of equity [16]. The recommendations below are influenced by the Guide, previous MAA publications, and feedback from a 2018 town hall meeting at the Joint Mathematics Meetings.

Recognizing that advising and correct placement are essential to students’ success and encourage them to continue in mathematics, the Mathematical Association of America (MAA) offers the following recommendations to mathematics departments:

A. Placement

1. Have established policies and procedures for placement in introductory mathematics courses. These policies should be well understood and clearly communicated to students and all who advise incoming students.

2. Use evidence beyond admission information for placement – SAT/ACT scores are not sufficient. Math departments and faculty should be involved in determining guidelines and protocols for placement in mathematics courses, including the appropriate use of placement testing. See [18] for more details.

3. Carefully advise and evaluate students entering with college credit, through dual enrollment, AP/IB, or transfer credits. Involve both the sending and receiving institutions, whenever possible. Maintain updated lists of courses from other local institutions that are accepted as transfer credit or that provide developmental coursework students may need outside your curriculum.

4. Periodically review the effectiveness of the placement tools and procedures, focusing both on DFW rates and future success of A/B students. The MAA specifically rejects the manipulation of DFW rates for any purpose.

B. Curricular Matters

5. Examine how well introductory and lower level courses are serving the needs of students. See [2] for a relevant case study, as well as communications from a 2019 workshop hosted by the National Academies of Sciences, Engineering, and Medicine [17].

6. Revisit prerequisite and co-requisite requirements on a regular basis to determine if the courses available are adequately meeting the placement needs of incoming students. Make curriculum decisions based on best practices. For examples, see the MAA Curriculum Guide [11].

C. Advising

7. Use informal and formal advising methods. Advising that supports institutional goals and is coordinated between faculty members and advising offices can be very effective. Advising should include contacting, early and often, any student who demonstrates warning signs of not being successful. This may be done through automated systems or individual outreach from faculty or advisors. For additional information on this topic, see [5].

8. Use proactive advising practices (also known as “intrusive advising”) that involve frequent contact with students with low performance or risk factors, as well as effective coordination between faculty and advising offices. These have been shown to be effective in reaching students and encouraging them to seek help when needed [5].

9. Assign every student who declares a major in the mathematical sciences an advisor from the mathematical sciences faculty. The faculty advisors should regularly meet with their advisees. Advisors should be aware of the influence they have in encouraging students, particularly those from underrepresented groups, to continue in mathematics. See [9] for more information on advising students toward graduate studies.

10. Promote the idea of a mathematics major to all students, recognizing the power of small encouragements and discouragements, especially in introductory courses. If possible, assign a faculty advisor or mentor to any student who shows interest in majoring in mathematics.

Students’ experiences in their mathematics courses often play a role in their decision to continue in the field. Departments should provide support for every level of student they serve, recognizing the changing population and varied backgrounds of students. MAA therefore offers the following recommendations to mathematics departments.

A. Support in Class

1. Ensure that courses have clear expectations, provide a variety of learning opportunities, and use evidence-based assessment tools to measure student learning.

2. Create classroom environments in which students’ contributions are valued and every student feels free to participate [19]. The classroom should be a safe place where all students can take risks to explore their understanding of course content. Encourage instructors to provide extra practice, problems that move students progressively toward stronger understanding (i.e., scaffolding), or challenge problems to meet students’ different academic needs.

3. Discuss student learning with faculty colleagues, and create opportunities in class for students to develop learning skills. Instructors should model and encourage good mathematical habits. Examples include working an easier but related problem, looking at examples, and avoiding looking at solutions too early in the problem-solving process.

B. Support Outside of Class

4. Work with Academic Services offices to recruit and train student tutors with appropriate background and skills. Schedule student support services to accommodate the schedules of many students, including those who commute or have job or family responsibilities.

5. Ensure that all faculty are familiar with disability resource office policies and support services to create a positive learning environment for all students. For more information, see [4, 20].

C. Implications for Curriculum and Staffing

6. Encourage faculty, including part-time faculty and graduate students serving as instructors, and particularly those teaching general education courses, to familiarize themselves with math anxiety and practices based on current research to support student learning. Resources like [3] may be helpful.

7. Understand and support the mathematical skills needed by students in other disciplines. See MAA resources [10, 11] for guidance.

8. Develop multiple mathematics pathways including calculus, statistics, and other non-calculus based quantitative reasoning courses. Details can be found in [12] for pre-calculus courses, [1] for introductory statistics courses, and [15] for quantitative reasoning courses.

9. Reflect on the ways the department is meeting all students’ needs in all courses, not just majors, when undergoing departmental assessment and program review.

Academic departments should recruit, encourage, and support students from underrepresented groups in all math courses. The achievement gap in both the major and in our general undergraduate population is real and important enough to warrant significant attention. The MAA, therefore, recommends the following strategies to build a culture of equity.

A. Recruitment of Students

1. Work with administration and admission offices to send recruiters to events at high schools with large populations of underrepresented groups and encourage faculty to align with high school faculty in underrepresented group communities through outreach and co-credit courses.

2. Invest time and effort to recruit and support returning adult students.

3. Identify and implement practices that bridge the gap between admitting a diverse student body and graduating a diverse student body. See, for example, [7].

B. Support in Class

4. Encourage flexibility in course policies, acknowledging that many students from underrepresented groups have jobs or are primary caregivers for their families.

5. As a department, learn about and discuss teaching practices that impact student learning, including practices that limit learning (e.g., that may arise from stereotype threat or implicit bias) and those that support learning (e.g., culturally relevant pedagogy and inclusive teaching practices). All departments, especially those in a predominantly white institution, need to make sure that students from underrepresented groups feel welcomed and that faculty use teaching practices that reflect access, flexibility, and openness. See resources such as [6], [8], [13], [22].

6. Identify and focus on students’ abilities and not their deficits, being aware that underrepresented groups tend to under-evaluate their own abilities. Intentionally give authentic encouragement and include positive and constructive feedback on assignments. Make intentional efforts to identify and reach out to students to invite them to consider majoring in mathematics. Create universal structures that welcome all students.

C. Impact on Faculty

7. Make a deliberate effort to hire faculty that make the department more diverse. Follow best practices for reaching underrepresented groups in the hiring process. These are outlined in Statement #1 from the MAA’s Committee on Faculty and Departments.

8. Value work that faculty do to recruit, retain, and mentor students in the faculty evaluation and promotion process and support them in their efforts to improve in this area. Departments are encouraged to identify and create a bank of resources for faculty which will enable them to support underrepresented groups.

D. Co-Curricular Support

9. Ensure that students encounter mathematicians from a variety of backgrounds, being aware that stereotypes of mathematicians can influence persistence [21]. Efforts could range from a speaker series to something less costly such as posters to showcase a diverse set of mathematicians.

10. Support student organizations in creating policies and organizing activities that support inclusion, encourage collaboration, and de-emphasize competition. Organizations should also be encouraged to invite diverse speakers and reach out to students from many backgrounds.

11. Guide advisors to help students, particularly first generation or those from underrepresented groups. Identify co-curricular organizations and mentors on campus that will connect the student with the campus community, even outside of mathematics.

12. Create or designate a physical space for informal student-to-student collaboration in the department. The goal is to encourage bonding, community building, and collaboration among mathematics majors [14].

13. Work with administration to create bridge programs to support students from underrepresented groups as they enter college and/or participate in these programs as faculty to welcome students to campus and to the mathematics program [2].

14. Coordinate events with campus multicultural groups, welcoming students from across campus to the mathematics program. Make a deliberate effort to include interested members of underrepresented groups in undergraduate research and internship opportunities.

1. American Statistical Association. Guidelines for Assessment and Instruction in Statistics Education (GAISE) in Statistics Education (GAISE), College Report. 2016. Retrieved from https://www.amstat.org/asa/education/Guidelines-for-Assessment-and-Instr…. Accessed 2019-09-09.

2. Ashley, M. et al. (2017). “Building Better Bridges into STEM: A Synthesis of 25 Years of Literature on STEM Summer Bridge Programs”, CBE Life Sci Educ. 2017 Winter; 16(4): es3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5749972/. Accessed 2019-09-09.

3. Brakke, David F., and Linda Cabe Halpern. “Improving Success of Students in Introductory Mathematics and Statistics Courses.” Peer Review 16.3 (2014): 13-16. Web.

4. Canu, W. H., Elizondo, M., & Broman-Fulks, J. (2017). History of ADHD traits related to general test and specific math anxiety in college students. Learning and Individual Differences, 58, 56-63. http://dx.doi.org/10.1016/j.lindif.2017.07.008. Accessed 2019-09-09.

5. Drake, Jayne K., Peggy. Jordan, and Marsha A. Miller. Academic Advising Approaches Strategies That Teach Students to Make the Most of College. 1st ed. San Francisco: Jossey-Bass, 2013.

6. Evans, R., Friedman, J., McGrath, L., Myers, P., & Ruiz, A. (2018). Math Path: Encouraging Female Students in Mathematics through Project-Based Learning. PRIMUS, 28(4), 287-299. https://doi.org/10.1080/10511970.2017.1339154. Accessed 2019-09-09.

7. Gomez, A., Cobian, K. P., & Hurtado, S. (2018). Improving STEM Degree Attainment Rates: Lessons from Hispanic Serving Institutions. Retrieved from https://heri.ucla.edu/pub/AERA-Lessons-from-Hispanic-Serving-Institution…. Accessed 2019-09-09.

8. Greer, M. L. (2019). Interdisciplinarity and Inclusivity: Natural Partners In Supporting Students. PRIMUS. https://doi.org/10.1080/10511970.2018.1488782. Accessed 2019-09-09.

9. McCoy, D. L., Luedke, C. L., & Winkle-Wagner, R. (2017). Encouraged or weeded out: Perspectives of students of color in the STEM disciplines on faculty interactions. Journal of College Student Development, 58(5), 657-673. http://dx.doi.org/10.1353/csd.2017.0052. Accessed 2019-09-09.

10. Mathematical Association of America. Math & Bio 2010: Linking Undergraduate Disciplines. 2005.

11. Mathematical Association of America. Curriculum Guide to Majors in the Mathematical Sciences. 2015. Retrieved from https://www.maa.org/node/790342. Accessed 2019-09-09.

12. Mathematical Association of America. College Algebra Guidelines. 2007. Retrieved from https://www.maa.org/sites/default/files/pdf/CUPM/crafty/CRAFTY-Coll-Alg-…. Accessed 2019-09-09.

13. Mathematical Association of America. Voices of the Partner Disciplines. Retrieved from https://www.maa.org/programs-and-communities/member-communities/curricul…. Accessed 2019-09-09.

14. Mathematical Association of America. Required Resources and Recommended Technology for College and University Mathematical Science Departments. 2018.

15. Mathematical Association of America | Tunstall L., Karaali G., and Piercey, V., Eds. (2019) Shifting Contexts, Stable Core: Advancing Quantitative Literacy in Higher Education. https://www.maa.org/press/ebooks/shifting-contexts-stable-core-advancing…. Accessed 2019-09-09.

16. Mathematical Association of America | Instructional Practices Guide. https://www.maa.org/programs-and-communities/curriculum%20resources/inst…. Accessed: 2019-09-19.

17. National Academies of Sciences, Engineering, and Medicine, 2019. Workshop and webcast: Increasing student success in developmental mathematics. https://sites.nationalacademies.org/DBASSE/BOSE/Developmental_Math/index…. Accessed 2019-09-09.

18. Ngo, Federick, and William Kwon. “Using Multiple Measures to Make Math Placement Decisions: Implications for Access and Success in Community Colleges.” Research in Higher Education 56.5 (2015): 442-70. Web.

19. Ramirez, G., McDonough, I. M., & Jin, L. (2017). Classroom stress promotes motivated forgetting of mathematics knowledge. Journal of Educational Psychology, 109(6), 812-825. http://dx.doi.org/10.1037/edu0000170. Accessed: 2019-09-19.

20. Thurston, L. P., Shuman, C., Middendorf, B. J., & Johnson, C. (2017). Postsecondary STEM Education for Students with Disabilities: Lessons Learned from a Decade of NSF Funding. Journal of Postsecondary Education and Disability, 30(1), 49-60. Retrieved from https://files.eric.ed.gov/fulltext/EJ1144615.pdf. Accessed: 2019-09-19.

21. Williams, M. J., George-Jones, J., & Hebl, M. (2018). The face of STEM: Racial phenotypic stereotypicality predicts STEM persistence by—and ability attributions about—students of color. Journal of Personality and Social Psychology, http://dx.doi.org/10.1037/pspi0000153. Accessed: 2019-09-19.

22. Zambrano, D. (2018). Equity oriented practices in a college level pre-calculus classroom (Doctoral dissertation, San Francisco State University). Retrieved from http://hdl.handle.net/10211.3/204079. Accessed: 2019-09-19.

Edward Aboufadel (CFD chair), Grand Valley State University
Mary Beisiegel, Oregon State University
Connie Campbell, Gulf Coast State College
Jill Dietz, St. Olaf College
Timothy Flowers, Indiana University of Pennsylvania
Debra Lynn Hydorn, University of Mary Washington
Tyler J. Jarvis, Brigham Young University
Audrey Malagon, Virginia Wesleyan University
Benedict K. Nmah, Morehouse College
Victor Piercey, Ferris State University
Emily E. Puckette, University of the South

March 2020

Acknowledgment: The committee thanks Ann Breitenwischer M.A., Mathematics Liaison Librarian, of Ferris State University for her work on the literature review.

Departments in the mathematical sciences should determine the content and implementation of their program to ensure equity and consistent educational quality. This requires clear communication, consistent programming, flexible pedagogies, and a supportive environment for students. The program and related policies should enable student-faculty interaction, particularly with regards to class size and regular feedback. Further recommendations on diversity, equity, and inclusion as they pertain to curriculum and teaching will be addressed in a future guideline statement.

a. Departments should have the primary responsibility in setting placement policies, prerequisites/corequisites, course content, and learning outcomes for departmental courses. (Related recommendations can be found in the MAA’s Guideline Statement #3, part I. — “Best Practices for Student Support” — placement and advising.).

b. Information about courses should be current and easily accessible in the course catalog and/or website. Course prerequisites and any policies on waiving prerequisites should be clearly stated. Current syllabi or extended course descriptions (i.e., documents that include course topics and objectives) for all courses should be available publicly for review by faculty colleagues and students. Courses that are not offered at least every two years should be clearly designated as such. If not offered within five years, a course should be removed from the course catalog.

c. Departments should plan course offerings to facilitate four-year graduation rates. Courses which are required in a student’s program of study should be scheduled and taught at least once every two years. If required courses cannot be offered at least once every two years, departments should reconsider the structure of their major or approve substitute requirements.

d. For all course transfer equivalencies from other institutions, departments should work with administrations to ensure that the appropriate equivalency is determined. Course equivalencies should be publicized to students and faculty. In cases where a department regularly teaches students who transfer from two-year colleges, the departmental faculty members at the institutions should work together to ensure compatibility of appropriate courses in content, technology and rigor.

e. Departments should have established procedures for periodic review of the curriculum. These reviews should include, but are not limited to, careful scrutiny of course content, prerequisites, texts, use of technology, and student learning outcomes. The curriculum should be examined within the context of departmental goals and institutional mission as well as with consideration of its relevance to and appropriateness for the students being served.

f. Courses that support other programs should be planned, implemented and reviewed in collaboration with client departments.

a. The mathematical sciences curriculum should be responsive to the needs of the students enrolled in any departmental course. Course and program offerings should provide suitable academic challenges and should be based on the expectation that all students can learn mathematics. The spectrum of beginning courses should be broad enough to offer appropriate choices and placement in mathematics for all students entering the institution [6,7].

b. No one method of instruction is optimal for all students, for all faculty members, or for all subject matter. The department should encourage and support faculty members who investigate, implement, and evaluate pedagogical techniques that show promise based on results of research on teaching and learning.

c. To encourage student-faculty interaction and enable faculty to give students individual attention, the department should work with its administration to limit class sizes to at most 30 students whenever possible [1,2,3,4,5]. Restricted class sizes also give faculty members greater flexibility in meeting their students’ needs and adopting instructional methods that best fit the content being taught.

d. Assessment of student performance is crucial for both students and instructors. The instructional staff assigned to each course should be sufficient to allow for regular and frequent feedback in a variety of forms (e.g., peer review, evaluative) to inform students about their progress. Frequent evaluation of students also provides important information that the course instructor can use to make mid-course adjustments in teaching or course design.

e. It is important to provide opportunities for students to formally and informally voice praise and concerns based on their learning experiences, at the conclusion of a course. Such feedback can be useful formatively to develop excellence in teaching. However, the use of student course evaluations of faculty for tenure and other decisions is complicated because of their known biases. (A collection of articles on the subject of bias in student evaluations is available.) Use of these evaluations in evaluation decisions requires careful examination in light of these biases. In addition, students aren’t and can’t be expected to be experts in evaluating teaching in the same way professional colleagues are.

a. Departments of mathematical sciences should employ technology in ways that foster teaching and learning, increase the students’ understanding of mathematical concepts, and prepare students for the use of technology in their careers or graduate study. Professional development needs to be offered to support the use of technology in teaching. Where appropriate, courses offered by the department should integrate current technology, such as computer algebra systems. (Related recommendations can be found in the MAA’s Guideline Statement #2, “Required Resources and Recommended Technology for College and University Mathematical Sciences Departments”.)

b. Special emphasis should be placed on giving prospective K-12 teachers the experience of learning mathematics aligned with methods practiced in schools. Prospective teachers should be educated to be leaders in the effective use of technology in the schools [6,7].

c. The department should develop and keep updated a general policy for assessment of student work that reflects the role of technology in the curriculum, and mathematics more generally, while taking into account those students that do not have access to computers or the Internet.

a. The curricula of bachelor’s degree programs in the mathematical sciences should be consistent with the current recommendations of the MAA Committee on the Undergraduate Program in Mathematics (CUPM) [7].

b. A major, minor or concentration in statistics, the program should be consistent with the current American Statistical Association recommendations in its Guidelines for Assessment and Instruction in Statistics Education (GAISE) [8].

c. If the department offers a program for pre-service teachers, such as a major or concentration in mathematics education, the program should reflect the recommendations of the Conference Board on Mathematical Sciences [9] and the guidelines of the National Council of Teachers of Mathematics [10].

d. d. A valuable resource for guidelines in mathematical modeling is the Guidelines for Assessment and Instruction in Mathematical Modeling Education, as published by COMAP and SIAM [11].

1. “Class Size Matters”, Stephen L. Benton and William H. Pallett, Inside Higher Ed,  January 29, 2013.  Available at:  https://www.insidehighered.com/views/2013/01/29/essay-importance-class-size-higher-education
2. “Increasing Student Success: Smaller Classes, Innovative Pedagogy at UCF”, Association of American Colleges & Universities (AACU), 2010.  Available at:  https://www.aacu.org/campus-model/increasing-student-success-smaller-classes-innovative-pedagogy-ucf
3. “Class Size Matters: Heterogeneous Effects of Larger Classes on College Student Learning”, Timothy M Diette & Manu Raghav, Eastern Economic Journal, 2014.  Available at:  https://link.springer.com/article/10.1057/eej.2014.31
4. “The Effectiveness of Class Size Reduction”, William J. Mathis, National Education Policy Center, 2016.  Available at:  https://nepc.colorado.edu/sites/default/files/publications/Mathis%20RBOPM-9%20Class%20Size.pdf
5. “The Impact of Class Size on Outcomes in Higher Education”, James Monks and Robert M. Schmidt, The B.E. Journal of Economic Analysis & Policy, 2011.  Available at:  https://scholarship.richmond.edu/economics-faculty-publications/49/
6. Instructional Practices Guide, Mathematical Association of America, 2017.
7. 2015 CUPM Curriculum Guide, Mathematical Association of America, 2015.
8. Guidelines for Assessment and Instruction in Statistics Education,  (GAISE), 2016.  Available at:  https://www.amstat.org/asa/education/Guidelines-for-Assessment-and-Instruction-in-Statistics-Education-Reports.aspx
9. The Mathematical Education of Teachers II, Conference Board of Mathematical Sciences (CBMS), 2012.  Available at:  https://www.cbmsweb.org/archive/MET2/met2.pdf
10. Principles to Actions: Ensuring Mathematical Success for All, National Council of Teachers of Mathematics (NCTM), 2014.  Available at https://www.nctm.org/PtA/
11. GAIMME: Guidelines for Assessment and Instruction in Mathematical Modeling Education, Second Edition, Sol Garfunkel and Michelle Montgomery, editors, COMAP and SIAM, 2019. Available at https://www.siam.org/Publications/Reports/Detail/guidelines-for-assessment-and-instruction-in-mathematical-modeling-education

Ed Aboufadel, Grand Valley State University
Emily Puckette, University of the South
Audrey Malagon, Virginia Wesleyan University
Mary Pilgrim, Colorado State University
Jason Douma, University of Sioux Falls
Benedict Nmah, Morehouse College
Jill Dietz, St. Olaf College
Tim Flowers, Indiana University of Pennsylvania
Debra Lynn Hydorn, University of Mary Washington

October 2020

Each department of mathematical sciences should participate at regular intervals in a process of program review or assessment. These program reviews should focus on internal reflection and improvement, though they may also be part of larger assessment and accreditation protocols. Through the standard cycle (typically between four and ten years) of planning and setting goals, prioritizing and implementing strategies, measuring progress, and reflection [5], departments can respond systematically to needs to update curriculum, pedagogy, technology, approaches to student success, and strategies to promote inclusion and equity. Helpful advice can be found on the MAA’s Committee on Program Review web page, including the Guidelines for Undertaking a Self-Study in the Mathematical Sciences [1] as well as from Hanover Research [3] and in MAA Focus [6].

Participants in the process should include department faculty at all ranks, students, alumni, client departments, deans and other appropriate administrative officials, and external mathematical sciences reviewers. Specific departmental faculty members should be assigned to lead the process, with at least one member of the leadership team having strengths in organization, evaluation, or management.

Reviewers, internal or external, should have sufficient disciplinary knowledge to engage with departmental faculty members and to understand the program’s mission. Guidelines for serving as a reviewer have been published by the MAA’s Committee on Program Review [2]. The cycle should include a self-study “to reflect on where the department has been, where it is now, and where it wants to be” [1]. The cycle should also include a strategic plan that is acceptable to the department and to its dean in order to move forward — enhancing strengths and addressing opportunities to improve identified in the planning and evaluation process.

The major components of the planning and evaluation process should include:

1) A statement that clearly defines the mission of the undergraduate mathematical sciences department.

2) A delineation of the educational goals of relevant curricula or programs, as well as a statement of how attainment of these goals is expected to fulfill the stated mission of the curricula.

3) Procedures for measuring the extent to which the educational goals are being met. These measures will, of necessity, be multi-dimensional since no single statistic can adequately represent departmental performance with respect to most departmental goals. Measures of student learning and other student outcomes should be included in the procedures. Advice regarding these measures has been published by the MAA Committee on Program Review [1].

4) A process for regularly reviewing (and revising, if necessary) departmental and academic program components in light of measurements of program success.

5) A departmental and institutional plan to procure and allocate, over time, the resources needed to implement the strategic plan agreed to by the department and its dean.

6) Consistency with institutional processes.

The periodic reviews should examine all aspects of the department’s undergraduate academic program. Main components of a review should include, but not be limited to, the following sections.

a. What is the relevant history of the department/program/curriculum (especially looking back to the time of the last review) and its relation to the college/university?

b. What is the mission of the department/program/curriculum and its student learning goals?

c. What are the resources (faculty, support staff, budget, facilities, technical support, library) of the department/program/curriculum?

a. In what ways does the department/program offer a curriculum that serves the general student body? Does this service meet the goals of the institution’s general education requirements? Does this service meet the needs of client departments/programs?

b. What are the curricular goals of the department/program/curriculum? How do the curricular offerings and the structure of the major support those goals, the mission of the department, and its student learning goals?

c. How does the department/program/curriculum judge curricular quality and effectiveness? On that basis, how well is the department/program/curriculum doing?

d. In what ways do the curriculum and structure of the major adhere to or deviate from the most recent CUPM recommendations [4]?

a. What is the department’s current student enrollment in each program? How has that changed over time? What trends are anticipated?

b. What is the department’s current student enrollment in general education courses and courses in support of other programs? How have they changed over time? What trends are anticipated?

c. What are the department’s current recruiting, retention, and advising practices? How effective are they, and how is that effectiveness judged?

d. What efforts are made to recruit, retain, advise, and support and students from underrepresented groups? How effective are these efforts, and how is that effectiveness judged?

e. What is the employment profile for graduates of the program? How satisfied are alumni/ae and their employers with their preparation in the program and their ability to find sustained employment or pursue advanced education in their field, and how is that satisfaction judged?

a. In what ways does the current faculty complement support departmental and institutional missions, including community engagement, university service, and national visibility?

b. Do current faculty (tenured, tenure-track, non tenure-track) complement meet departmental and institutional needs for diversity and representation? If not, what needs are anticipated?

c. What needs are anticipated or currently unmet in terms of specific sub-discipline representation and support for faculty scholarship and professional engagement?

a. What assessment evidence is there to address the components already listed above?

b. Further components questions to consider to measure program quality may include:

i) How have students performed in seminars, departmental comprehensive examinations, course-embedded assessment, undergraduate research activities, internships, consulting experiences, and national competitions and examinations?

ii) What is the opinion of students, obtained through surveys and interviews? (These should address the program broadly, and not individual instructors.)

iii) What accomplishments and awards have been received by the current students and graduates of the department’s programs, as well as the department faculty?

iv) How do numbers of mathematical sciences majors and alumni compare to peer departments and to national averages?

v) How well do associate degree recipients who transfer to four-year colleges succeed in your program? Alternatively, what is the success of these recipients that transfer to your four-year program?

vi) How well do bachelor’s degree recipients succeed in graduate programs and other post-graduate opportunities?

vii) How well do underrepresented minorities (URMs) succeed in your program? How well do URMs who graduate from your program succeed in graduate programs and other post-graduate opportunities?

[1] Guidelines for Undertaking a Self-Study in the Mathematical Sciences, MAA Committee on Program Review, 2010.

[2] Guidelines for Serving as a Consultant in the Mathematical Sciences, MAA Committee on Program Review, 2010.

[3] Best Practices in Academic Program Review, Hanover Research, 2012.  Available at:  https://cpb-us-w2.wpmucdn.com/www.paulsmiths.edu/dist/6/103/files/2017/06/FD_HanoverResearch_BestPractices_ProgramReview-1c7556t.pdf

[4] 2015 CUPM Curriculum Guide to Majors in the Mathematical Sciences, MAA Committee on the Undergraduate Program in Mathematics, 2015.

[5] “Ways to Approach the Quality Improvement Process”, The CAHPS Ambulatory Care Improvement Guide: Practical Strategies for Improving Patient Experience, Consumer Assessment of Healthcare Providers and Systems (Agency for Healthcare Research and Quality), 2016.  Available at:  https://www.ahrq.gov/cahps/quality-improvement/improvement-guide/4-approach-qi-process/index.html

[6] “Getting Started with Program Review”, Walker, H., MAA Focus, June/July 2020.  Available at:  http://digitaleditions.walsworthprintgroup.com/publication/?m=7656&i=663226&p=20

Ed Aboufadel, Grand Valley State University
Emily Puckette, University of the South
Audrey Malagon, Virginia Wesleyan University
Mary Pilgrim, Colorado State University
Jason Douma, University of Sioux Falls
Benedict Nmah, Morehouse College
Jill Dietz, St. Olaf College
Tim Flowers, Indiana University of Pennsylvania
Debra Lynn Hydorn, University of Mary Washington

October 2020

This statement, informed by the references provided below, aims to address the needs of mathematics departments with regards to establishing and maintaining an environment supportive of diversity and the implementation of equitable and inclusive practices. The MAA recognizes that Black, Indigenous, and Latinx/Hispanic people, women, and individuals who have disabilities have been historically excluded from mathematics in the United States and as such are vastly underrepresented in the field. In addition, racism broadly and negatively affects people of color both domestic and international, and bigotry negatively impacts LGBTQIA+ individuals. In this statement, we will use the terms “underrepresented” and “underserved” to refer to faculty and students from the aforementioned groups, while acknowledging that this status is a direct result of years of systematic exclusion. We recognize that our understanding of who has been underserved will continue to evolve. We further acknowledge that while some of the challenges of underrepresentation in mathematics departments are similar among the various groups, each group also faces unique challenges, and there is a complex intersectionality among people’s identities.

Statement 1 from the MAA Committee on Faculty and Departments, published in 2017, addresses best practices in recruiting, retaining, developing, and evaluating faculty in college and university mathematical sciences departments. The MAA recognizes that certain groups are historically underrepresented in the mathematical sciences at the faculty level and it is the responsibility of every department to intentionally pursue diversity by actively engaging in practices that can lead to diversification of the profession. In this statement, we aim to give further guidance specific to the recruitment of mathematics faculty from underrepresented groups and support to those from underserved groups.

1. Recruitment
   In terms of recruitment, the following best practices were drawn from a variety of sources.
   1. Before the search begins, departments should:
      1. Evaluate the department’s composition — what are its strengths and challenges?  Conversations about the department’s diversity and how it is perceived by students and others internal and external to the department can lead to a common understanding and can help avoid tokenism.
      2. Train the search committee on implicit bias in relation to search and hiring practices and/or have a “equity advocate” as a committee member. This should be done before the vacancy announcement has been written to support members in crafting an inclusive job description.
      3. Clarify search committee rubrics, policies, and procedures before advertisements are placed and applications come in.
      4. Create a search committee composed of members who are open to using best practices guidelines for recruiting faculty from underrepresented groups to inform the search.
      5. Search as broadly as possible in order to attract a large and diverse applicant pool. For example, instead of searching for a stable homotopy theorist, consider opening the search up to topologists; instead of searching for a topologist, open the search up to a “theoretical” mathematician; instead of searching for a theoretical mathematician, open the search up to the best teacher who can support a diverse student body.
      6. Expand the search criteria to include experience mentoring underrepresented students and/or ability to contribute to diversity, equity, and inclusion (DEI) efforts on campus.
      7. Intentionally seek candidates who have a track record of mentoring underrepresented students.
   2. For the search, departments should:
      1. Advertise widely, using information from the AMS on PhDs earned to target institutions where underrepresented graduates have obtained degrees. Places to consider advertising include the National Association of Mathematicians (NAM), the Association for Women in Mathematics (AWM), and the Center for Minorities in the Mathematical Sciences (CMMS). Seek out applicants from institutions known for graduating underrepresented PhDs, including HBCUs.
      2. Highlight institutional values and activities regarding DEI in job advertisements, along with any initiatives designed for faculty support (such as family-friendly policies).
      3. Obtain institutional funding for members of the search committee to travel to conferences and other recruiting events, including those that attract applicants from underrepresented groups.
      4. Develop strategies based on inclusion rather than exclusion. For example, rather than whittling down a list of applicants by excluding those with limited teaching experience, instead look to include those applicants with demonstrated effectiveness at supporting students whether through teaching, mentoring, or some other means.
      5. Keep data on applications, especially regarding underrepresented applicants, and then review it to see if it matches the department’s goals for applications, interviews, and hiring.
      6. Incorporate some flexibility in whom candidates meet with when they come to campus. There will be a set predetermined list (e.g., Provost, Chair, department members), but ask candidates who else they might want to talk to (e.g., other women; Black, Indigenous, or People of Color (BIPOC); or LGBTQ+ folks) during the interview process.
2. Retention
   It is not enough to simply hire a faculty member from a historically underrepresented group. The department and institution must work collaboratively to ensure that the faculty member is supported throughout their career. Again, the following best practices were drawn from a variety of sources, available below.
   1. Develop policies that are supportive of underrepresented faculty such as:
      1. Family-friendly policies in the department and institution that value a work-life balance.
      2. Reduced dependency on student evaluations, as there is evidence that they are biased against underrepresented groups [1, 2].
      3. Tenure, promotion, and annual review measures that support DEI scholarly and service activities and recognize the substantial bias in evaluations of women and BIPOC faculty members. Activities might include:
         1. Participating in professional development focusing on DEI
         2. Using effective teaching methods that promote DEI
         3. Engaging in scholarship that focuses on DEI in mathematics and/or mathematics for DEI
         4. Organizing or participating in outreach focusing on DEI
         5. Formal and informal mentoring of underrepresented students
   2. Develop a robust mentoring program both in the department and at the institution. Underrepresented faculty will benefit from engaging with mathematics colleagues and fellow underrepresented faculty mentors to help them navigate the institution. While there might be one or two official mentors, be clear that supporting departmental faculty – especially faculty from underrepresented groups — is the responsibility of the entire department, not just the mentors and/or chair.
   3. Develop norms for behavior and decision-making processes at department meetings that contribute to a supportive environment, and articulate these in writing.
      1. Behavior norms might include arriving on time, not talking over people, recognizing each person’s contributions, being truly present and not doing other work during meetings.
      2. Decisions might be entirely in the hands of the chair, arrived at by vote (by all members, just tenured members, or another method), or tabled until consensus is reached. Whatever the method, the details should be known by all in the department.
   4. Celebrate accomplishments in teaching, scholarship, and service informally by mentioning them at a meeting, or stopping by someone’s office for a chat.
   5. Provide all faculty with periodic cultural awareness and sensitivity training. Host workshops, seminars, or colloquia on DEI.
   6. Be aware that underrepresented faculty are often called upon to do more committee work, service work, and mentoring than other faculty members, which can detract from the scholarly activity necessary for promotion.
      1. More senior faculty (e.g. the department chair) can help new underrepresented faculty set appropriate boundaries to guard their time — perhaps by providing clear guidelines about the level of service that is expected and providing a buffer between the administration and the faculty member if the administration or other colleagues are asking too much [3].
      2. Some underrepresented faculty find that institutional service helps form much needed community for retention, survival, or creative research. Implement programs which allow interested faculty to earn course release or stipends for such work.
      3. Within a department, the work of justice, equity, diversity, and inclusion belongs to all department members, not just to underrepresented faculty.

MAA-CFD Statement 3 and Statement 5, both published in 2020, address general issues of student recruitment and support, while this statement more specifically addresses departmental policies and practices regarding the recruitment, retention, and academic success of traditionally underrepresented students. For historically underrepresented minorities, departments should focus on preparation, access and motivation, financial aid advocacy, academic support, and social integration [4]. In the following, we provide recommendations for departments to revisit their recruitment, placement, teaching, and curricular practices to address any potential gaps in creating an inclusive environment for underrepresented students.

1. Recruiting Students from Underrepresented Groups
   Departments are encouraged to approach recruitment offices at their institutions to explicitly discuss any existing gaps in recruiting mathematics (or mathematics-related) majors who have been historically excluded from the field. As many recruitment offices focus on obtaining a larger number of students, it might be a department’s responsibility to shed light on recruiting more underrepresented students.
2. Placement Practices
   We recommend departments examine the ways in which existing placement practices and tools disadvantage underrepresented students [5]. After identifying any existing marginalizing placement practices, departments should address the issues by adopting tested and evidence-based practices that support the success of underrepresented students [6]. This might include placing students in co-requisite support courses rather than relying on traditional notions of prerequisite coursework.
3. Advising and Mentoring
   1. Departments are encouraged to review advising materials and processes to address implicit biases in how underrepresented students are advised academically. For instance, they may be advised to choose “easy” electives during course selection. They may not be frequently made aware of internship and REU opportunities, encouraged to take on mentored research, or recommended to consider graduate study. Departments should also encourage academic advisors to attend workshops on implicit bias and its impact on underrepresented students’ success.
   2. As advising plays a huge role in underrepresented students’ success, we additionally recommend the formation of a special network of advisors from departments and First Year Success Centers to focus their efforts on securing successful mentoring and advising for underrepresented students.
   3. Mentoring initiatives can be a powerful tool for student support. Mentoring of students can be done by both faculty and peers, perhaps pairing first-year students with upper level majors.
4. Building a Supportive Environment
   1. Learning to Advocate for Underrepresented Students: Departments are encouraged to have regular departmental teaching circles, seminars, and/or book clubs. These are reflective opportunities for faculty to address any particular needs that might come up when advocating for marginalized students [7].
   2. Increasing Visibility of Underrepresented Mathematicians: Departments should make an effort to recruit mathematicians from marginalized groups to speak at departmental colloquia or other events. Websites like Lathisms, Mathematically Gifted and Black, Indigenous Mathematicians, Spectra, and the Association for Women in Mathematics could serve as a starting point for identifying speakers or connecting students to further resources and support.
   3. Establish a Welcoming Community within the Department: In addition to peer and faculty mentoring for students, a sense of community can be established through departmental meet-and-greets for majors and minors, student clubs or organizations, book clubs, game nights, collaborative problem-solving, student-faculty research projects, and group volunteering.
   4. Connecting Underrepresented Students to Internal and External Support: Faculty should familiarize themselves with other opportunities for supporting marginalized students.  Most campuses have inclusion-based centers, sometimes called social justice centers, that faculty can help students connect with.  Externally, departments might purchase departmental memberships to professional organizations (e.g. Association for Women in Mathematics; National Association of Mathematicians; Society for Advancement of Chicanos and Native Americans in Science) to facilitate networking, mentorships, REUs, scholarships, conferences, and post-baccalaureate educational opportunities for marginalized students.
5. Evaluation
   Departments should establish program review measures (e.g. MAA-CFD Statement 5; MAA Committee on Program Review) for recruiting, tracking, mentoring, and advising of students, including those from underrepresented groups.  Data gathered should inform departmental decision-making.

MAA-CFD Statement 4, published in 2020, introduces general best practices for mathematics curriculum and teaching.  The following provides more detail about the curriculum and pedagogy that supports underrepresented students. Departments in the mathematical sciences should determine the content and implementation of their program to ensure equitable and inclusive pedagogy. This requires that all students have access to high-quality mathematics curriculum, effective teaching and learning, high expectations, and the support and resources needed to maximize their learning potential [8]. Following are guidelines for cultivating equitable and inclusive education environments.

1. Teaching
   1. Consider adopting research-based instructional practices that have been shown to foster success for underrepresented students.
      1. Inclusive [9], active learning (AL) [10], and anti-deficit pedagogical practices [11] allow underrepresented students’ voices to be heard.
      2. AL techniques create supportive learning environments that lead to higher achievement for members of groups that are traditionally underrepresented in mathematics [10, 12, 13], provided that careful attention is paid to group dynamics.
      3. Social justice pedagogy [14] and responsive, culturally relevant pedagogy recognizes how students learn, what they are passionate about, and what they are interested in.
   2. Set, communicate, and maintain classroom norms that allow all voices to be heard and respected. Additionally, the following are recommended:
      1. Establish transparent rules.
      2. Establish fair grading using rubrics (e.g., include exceeds, meets, and does not meet expectations).
      3. Provide timely feedback and assessment consistently and regularly.
   3. Invest time and resources to:
      1. Educate faculty on effective AL techniques.
      2. Educate faculty on implicit bias and best practices to ensure educators address their own assumptions about different behaviors so judgment does not occur in the classroom and departmental workspaces.
      3. Support faculty participating in social and racial justice workshops and conferences.
      4. Reward faculty for collaborating with institutional centers for innovative teaching and learning and centers for equity, diversity, and inclusion.
   4. Strategize, develop, and implement policies, models and programming that address racial discrimination and systemic racism (for example, the MSRI Workshop on Mathematics and Racial Justice 2021).
2. Curriculum
   1. Be aware of common curricular practices that might drive student attrition from STEM majors, such as the traditional model of prerequisite developmental mathematics courses described in Part IIB. The Dana Center provides a toolkit [6] for effectively implementing corequisite support courses.
   2. Train individuals on DEI best practices and form a team of four to five (including, at minimum, one external mathematician, one woman, and one BIPOC) to perform an equity curriculum audit. Guidelines should be established that incorporate data from social justice studies and knowledge of inclusive curriculum.

[1] “Sexism, Racism, Prejudice, and Bias: A Literature Review and Synthesis of Research Surrounding Student Evaluations of Courses and Teaching,” Troy Heffernan, Assessment & Evaluation in Higher Education, 2021. Available at https://www.researchgate.net/publication/349864729_Sexism_racism_prejudi…

[2] “Exploring Bias in Student Evaluations: Gender, Race, and Ethnicity”, K. Chávez & K. Mitchell, PS: Political Science & Politics, 53(2), 2020. Available at https://www.cambridge.org/core/journals/ps-political-science-and-politic…

[3] Equity-Minded Faculty Workloads: What We Can and Should Do Now, K. O’Meara, D. Culpepper, D. Misra, & A. Jaeger, ACE-ENGAGE Report, January 8, 2021.  Available at https://www.acenet.edu/Documents/Equity-Minded-Faculty-Workloads.pdf

[4] Expanding Underrepresented Minority Participation: America’s Science and Technology Talent at the Crossroads, Committee on Underrepresented Groups and the Expansion of the Science and Engineering Workforce Pipeline; Committee on Science, Engineering, and Public Policy; Policy and Global Affairs; National Academy of Sciences; National Academy of Engineering; and Institute of Medicine, 2010.
https://www.nap.edu/catalog/12984/expanding-underrepresented-minority-pa…

[5] “More Than Just Skill: Examining Mathematics Identities, Racialized Narratives, and Remediation Among Black Undergraduates”, G.V. Larnell, Journal for Research in Mathematics Education, 47(3), 2016.
https://www.nctm.org/Publications/Journal-for-Research-in-Mathematics-Ed…

[6] A Call to Action to Improve Math Placement Policies and Processes, L. Couturier & J. Cullinane, The Charles A. Dana Center, 2015.  Available at https://www.jff.org/resources/call-action-improve-math-placement-policie…

[7] Asked and Answered: Dialogues On Advocating For Students of Color in Mathematics, P. E. Harris, & A. Winger, 2020.
https://www.pamelaeharris.com/post/new-book-on-advocating-for-students-o…

[8] Principles to Actions: Ensuring Mathematical Success for All, National Council of Teachers of Mathematics (NCTM), 2014.  https://www.nctm.org/PtA/

[9] “Encouraged or weeded out: Perspectives of students of color in the STEM disciplines on faculty interactions”, D.L. McCoy, C. L. Luedke, & R. Winkle-Wagner, R. Journal of College Student Development, 58(5), 2017. https://dx.doi.org/10.1353/csd.2017.0052

[10] “Active Learning Narrows Achievement Gaps for Underrepresented Students in Undergraduate Science, Technology, Engineering, and Math”, E.J. Theobald, M.J. Hill, E. Tran, et al, PNAS,117(12), 2020. Available at https://www.pnas.org/content/pnas/117/12/6476.full.pdf 

[11] “Anti-deficit Narratives: Engaging the Politics of Research on Mathematical Sense Making”, A.P. Adiredja, Journal for Research in Mathematics Education, 50(4), 2019.
https://www.nctm.org/Publications/Journal-for-Research-in-Mathematics-Ed…

[12] Active Learning in Post-Secondary Mathematics Education, Braun et al, Report from the Conference Board of the Mathematical Sciences, 2016. Available at https://www.cbmsweb.org/2016/07/active-learning-in-post-secondary-mathem…

[13] “Supporting High Achievement in Introductory Mathematics Courses: What We Have Learned from 30 Years of the Emerging Scholars Program”, E. Hsu, T.J. Murphy, U. Treisman, in Carlson and Rasmussen (Eds.) Making the Connection: Research and Teaching in Undergraduate Mathematics Education, MAA Notes #73, 2008.

[14] “Critical and Social Justice Pedagogies in Practice”, M. Breunig, in M.A. Peters (Ed.). Encyclopedia of Educational Philosophy and Theory, 2016. Available at https://www.marybreunig.com/assets/files/Critical-and-Social-Justice-Ped…

AMATYC:

https://amatyc.org/page/PositionDiversityEquityInclusion 

AMS:

http://www.ams.org/mathsafe/ams-mathsafe 

http://www.ams.org/about-us/governance/policy-statements/welcoming-envir…

https://www.ams.org/about-us/governance/policy-statements/anti-harassmen…

https://www.ams.org/about-us/edi-reporting 

http://www.ams.org/about-us/diversity

ASA:

https://www.amstat.org/ASA/Meetings/Meeting-Conduct-Policy.aspx?hkey=10b…

https://www.amstat.org/asa/files/pdfs/JEDI-Statement.pdf?v=1.0 

https://www.amstat.org/ASA/News/ASA-Announces-New-Anti-Racism-Task-Force…

AWM:

https://awm-math.org/policy-advocacy/welcoming-environment/ 

NCTM:

https://www.nctm.org/Standards-and-Positions/Position-Statements/Access-…

https://www.nctm.org/News-and-Calendar/News/NCTM-News-Releases/Statement…

SIAM:

https://www.siam.org/about-siam/policies-guidelines/detail/statement-on-…

Supporting Each and Every Student: Equity and Diversity (NCTM)
https://www.nctm.org/conferences-and-professional-development/Tips-for-T…

A Pathway to Equitable Math Instruction; Dismantling Racism in Mathematics Instruction
https://equitablemath.org/wp-content/uploads/sites/2/2020/11/1_STRIDE1.pdf

Inclusive Teaching (Bryan Dewsbury and Cynthia J. Brame)
https://www.lifescied.org/doi/full/10.1187/cbe.19-01-0021

Towards a Fully Inclusive Mathematics Profession (AMS, 2021)
http://www.ams.org/about-us/Towards-a-Fully-Inclusive-Mathematics-Profes…

Racial and Social Justice are Education Justice (NEA)
https://www.nea.org/advocating-for-change/racial-social-justice

The Impact of COVID-19 on Undergraduate Mathematical Sciences Education: Report on a CBMS Survey
http://www.ams.org/profession/data/cbms-survey/CBMS-COVID-Survey-Final-R…

Equitable Teaching Practices in IM 6–12 Math (Tina Cardone)
https://illustrativemathematics.blog/2020/08/11/equitable-teaching-pract…

Inclusive Practices in Mathematics Education
https://www.researchgate.net/publication/303772428_Inclusive_Practices_i…

Roadmap for Equitable and Effective Teaching, Learning, and Leadership in TK-12 Mathematics
https://www.rcoe.us/home/showpublisheddocument?id=2830

MAA Code of Conduct In Support of a Welcoming and Inclusive Community
https://www.maa.org/about-maa/policies-and-procedures/maa-code-of-conduct

Justice, Equity, Diversity, and Inclusion (JEDI) — American Statistical Association
https://magazine.amstat.org/blog/2020/10/01/jedi/

Inclusivity in Statistics and Data Science Education (Jeff Whitmer)
https://www.tandfonline.com/doi/full/10.1080/26939169.2021.1906555

Conversation for the Math Community — Equity in Action (MAA)
http://info.maa.org/pages/1780913/23513

Retaining Students in STEM majors
https://www.jstor.org/stable/43631580
TPSE: Creating Opportunities in Mathematics through Equity and INclusion (COME-IN) https://www.tpsemath.org/projects 

All web resources accessed October 24, 2021.

Ed Aboufadel (CFD chair, 2016-2022), Grand Valley State University
Erin Moss, Millersville University
Jill Dietz, St. Olaf College
Debra Lynn Hydorn, University of Mary Washington
Benedict Nmah, Morehouse College
Emily Puckette, University of the South
Mark Daniel Ward, Purdue University
Houssein El Turkey, University of New Haven
Carrie Diaz Eaton, Bates College
Dandrielle Lewis, High Point University
Christopher Dale Goff, University of the Pacific

Comments about MAA-CFD statements can be sent to the chair of the committee, Dr. Jill Dietz, St. Olaf College.  (dietz@stolaf.edu)