We found 10 results that contain "discrimination"
Posted on: #iteachmsu
Grading & Giving Feedback
Edit a Question During its Availability
Occasionally, a test question will need to be edited while an exam is in progress.
Quizzes – Manually Grade a Quiz - Instructor
Short answer questions, although auto-graded by D2L, should be double-checked for grading accuracy.
D2L Assessment Analytics
Examining quiz question statistics can help instructors determine if a question is too easy, too challenging, or needs editing for clarification.
The following is a quick guide for D2L Quiz and Grade Item statistics to help you monitor and improve your assessment questions and results.
D2L Quiz Statistics
To see how students performed overall on each of the quizzes, in your own course go to Assessments > Quizzes > Statistics (click on Statistics from the tab view across the top).
This list displays all of your course quiz averages.
Click on a quiz to see more details including User Stats, Question Stats, and Question Details.
Question Stats
The Question Stats list the Standard Deviation, Discrimination Index, and Point Biserial value for each question.
You can click on the link, "What do the statistics on this page mean?" above the table in your course to learn more. The information is also copied below.
What do the statistics on this page mean?
All statistics are calculated based on each user’s first attempt on the quiz. If a question is changed after attempts have been made, only the attempts on the newest version of the question are included in the statistics (ie. First attempts made before a question was changed are not included in the statistics for that question).
STANDARD DEVIATION
The standard deviation indicates how much scores vary from the average, ranging from 0% to 100%. A high standard deviation indicates that scores are spread out from the average, whereas a low standard deviation indicates that scores are close to the average.
DISCRIMINATION INDEX
The discrimination index indicates how well a question differentiates between high and low performers. It can range from -100% to 100%, with high values indicating a “good” question, and low values indicating a “bad” question.
POINT BISERIAL CORRELATION COEFFICIENT
The point biserial correlation coefficient is an analysis only applied to multiple choice and true/false question types that have only one answer with weight 100%, and all others with weight 0%.
Similarly to the discrimination index, the point biserial correlation coefficient relates individuals’ quiz scores to whether or not they got a question correct. It ranges from -1.00 to 1.00, with high values indicating a “good” question, and low values indicating a “bad” question.
*Note that only first attempts are included in that question's statistics.
Question Details
This tab will show you the summary of student responses for each question. If you notice a low or negative value for the Point Biserial or Discrimination Index, you may want to investigate the question. It could indicate a badly worded question or improperly keyed question answer.
For more, view the video tutorial on Generating Reports in D2L Learning Environment opens in new window. Currently, the statistics do not display for random "pool item" question types. Contact the MSU Service Desk to check on obtaining reports through the Data Hub.
Grade Item Statistics
To view grade item stats, in your own course go to, Assessments > Grades > (Grade Item) View Statistics – Use the pull down menu by a grade item title and select Statistics to display Class and User Statistics. If you have a grade scheme setup to display, you will also see the grade distribution chart on the page.
Working with student data
Keep the MSU Institutional Data Policy opens in new window in mind when storing data and making reports public in order to protect the security and confidentiality of student data.
Read more about best practices for handling data at secureit.msu.edu/data opens in new window from MSU IT Services – Academic Technology.
Addressing Issues of Academic Misconduct
What should you do if you discover cheating in your course? Follow the link to find out more.
What is an Academic Dishonesty Report
If you give a penalty grade as a result of academic misconduct, you must submit an Academic Dishonesty Report (ADR) to the university. See the link above as an example.
Occasionally, a test question will need to be edited while an exam is in progress.
Quizzes – Manually Grade a Quiz - Instructor
Short answer questions, although auto-graded by D2L, should be double-checked for grading accuracy.
D2L Assessment Analytics
Examining quiz question statistics can help instructors determine if a question is too easy, too challenging, or needs editing for clarification.
The following is a quick guide for D2L Quiz and Grade Item statistics to help you monitor and improve your assessment questions and results.
D2L Quiz Statistics
To see how students performed overall on each of the quizzes, in your own course go to Assessments > Quizzes > Statistics (click on Statistics from the tab view across the top).
This list displays all of your course quiz averages.
Click on a quiz to see more details including User Stats, Question Stats, and Question Details.
Question Stats
The Question Stats list the Standard Deviation, Discrimination Index, and Point Biserial value for each question.
You can click on the link, "What do the statistics on this page mean?" above the table in your course to learn more. The information is also copied below.
What do the statistics on this page mean?
All statistics are calculated based on each user’s first attempt on the quiz. If a question is changed after attempts have been made, only the attempts on the newest version of the question are included in the statistics (ie. First attempts made before a question was changed are not included in the statistics for that question).
STANDARD DEVIATION
The standard deviation indicates how much scores vary from the average, ranging from 0% to 100%. A high standard deviation indicates that scores are spread out from the average, whereas a low standard deviation indicates that scores are close to the average.
DISCRIMINATION INDEX
The discrimination index indicates how well a question differentiates between high and low performers. It can range from -100% to 100%, with high values indicating a “good” question, and low values indicating a “bad” question.
POINT BISERIAL CORRELATION COEFFICIENT
The point biserial correlation coefficient is an analysis only applied to multiple choice and true/false question types that have only one answer with weight 100%, and all others with weight 0%.
Similarly to the discrimination index, the point biserial correlation coefficient relates individuals’ quiz scores to whether or not they got a question correct. It ranges from -1.00 to 1.00, with high values indicating a “good” question, and low values indicating a “bad” question.
*Note that only first attempts are included in that question's statistics.
Question Details
This tab will show you the summary of student responses for each question. If you notice a low or negative value for the Point Biserial or Discrimination Index, you may want to investigate the question. It could indicate a badly worded question or improperly keyed question answer.
For more, view the video tutorial on Generating Reports in D2L Learning Environment opens in new window. Currently, the statistics do not display for random "pool item" question types. Contact the MSU Service Desk to check on obtaining reports through the Data Hub.
Grade Item Statistics
To view grade item stats, in your own course go to, Assessments > Grades > (Grade Item) View Statistics – Use the pull down menu by a grade item title and select Statistics to display Class and User Statistics. If you have a grade scheme setup to display, you will also see the grade distribution chart on the page.
Working with student data
Keep the MSU Institutional Data Policy opens in new window in mind when storing data and making reports public in order to protect the security and confidentiality of student data.
Read more about best practices for handling data at secureit.msu.edu/data opens in new window from MSU IT Services – Academic Technology.
Addressing Issues of Academic Misconduct
What should you do if you discover cheating in your course? Follow the link to find out more.
What is an Academic Dishonesty Report
If you give a penalty grade as a result of academic misconduct, you must submit an Academic Dishonesty Report (ADR) to the university. See the link above as an example.
Authored by: Casey Henley & Susan Halick
Assessing Learning
Posted on: Spring Conference o...
Implementation of the SPLEP and SPLS
Primary Presenter: Peter SavolainenCo-Presenters: VariousFormat: WorkshopDescription:This presentation was aimed at disseminating information about MSU's transition to a new Student Perceptions of Learning Environments Policy (SPLEP) and an associated Student Perceptions of Learning Survey (SPLS). The goals of the SPLEP are to support high-quality instruction by providing:
instructors and academic programs with data about student perceptions related to instructional practices to support course improvement in MSU’s teaching and learning environments;
instructional supervisors with one source of information for consideration in personnel decisions such as retention, promotion, salary, and tenure in recognition that effective teaching constitutes an important criterion in evaluating personnel; and
students with information to guide decision-making related to course selection.
In addition to outlining the policy, guidance was also be provided as to a set of institution-level questions for the SPLS that were developed based upon discussion of feedback submitted from across the university. These questions were developed with emphases on the following priorities:
Expectations are clear
Course is organized
Atmosphere promotes learning
Students have an opportunity to demonstrate understanding
Students gain knowledge
Students are engaged (course-created engagement)
The SPLS includes a series of questions that will provide student-facing information that can be especially useful when selecting courses. Discriminant validity- questions are also included, making it possible to determine the extent to which items meant to capture feedback about the quality of instruction are distinct from factors that are outside of the control of the instructor, such as:
Prior level of interest
Perceived workload
The presentation also included a discussion as to what the results do (not) mean, as well as how the feedback can be used to improve the quality of instruction broadly across the university. Concerns as to the potential (mis-) use of the data from a performance evaluation perspective will also be discussed.
Click here to view on MediaSpace
instructors and academic programs with data about student perceptions related to instructional practices to support course improvement in MSU’s teaching and learning environments;
instructional supervisors with one source of information for consideration in personnel decisions such as retention, promotion, salary, and tenure in recognition that effective teaching constitutes an important criterion in evaluating personnel; and
students with information to guide decision-making related to course selection.
In addition to outlining the policy, guidance was also be provided as to a set of institution-level questions for the SPLS that were developed based upon discussion of feedback submitted from across the university. These questions were developed with emphases on the following priorities:
Expectations are clear
Course is organized
Atmosphere promotes learning
Students have an opportunity to demonstrate understanding
Students gain knowledge
Students are engaged (course-created engagement)
The SPLS includes a series of questions that will provide student-facing information that can be especially useful when selecting courses. Discriminant validity- questions are also included, making it possible to determine the extent to which items meant to capture feedback about the quality of instruction are distinct from factors that are outside of the control of the instructor, such as:
Prior level of interest
Perceived workload
The presentation also included a discussion as to what the results do (not) mean, as well as how the feedback can be used to improve the quality of instruction broadly across the university. Concerns as to the potential (mis-) use of the data from a performance evaluation perspective will also be discussed.
Click here to view on MediaSpace
Authored by: Peter Savolainen, et al.
Pedagogical Design
Posted on: #iteachmsu
Office of Institutional Equity
If a student discloses that they have experienced discrimination or harassment, you must refer them to the Office of Institutional Equity. The Office of Institutional Equity (OIE) reviews concerns related to discrimination and harassment based on age, color, gender, gender identity, disability status, height, marital status, national origin, political persuasion, race, religion, sex, sexual orientation, veteran status and weight under the University's Anti-Discrimination Policy (ADP) and concerns of sexual harassment, sexual assault, stalking, dating violence, domestic violence, and other forms of sexual misconduct under the Relationship Violence and Sexual Misconduct and Title IX (RVSM) Policy.
A student can file a report here.
Confidential reporting for students
There are a number of resources on campus that can provide a confidential space where students can explore their options, talk about what happened, and obtain support services. Individuals often find it difficult to speak about what happened. Talking with someone once, or receiving ongoing support, can aid in recovery and assist with safety planning. If students access these services, they will be directed to other needed resources. These private and confidential resources are available at no cost. These services are not required to report incidents to the Office of Institutional Equity or campus police.
A student can access confidential resources here.
Mandatory reporting for faculty and staff
All University “responsible employees” and volunteers who are not otherwise exempted by this policy and/or applicable law must promptly report incidents of relationship violence, sexual misconduct, stalking, and retaliation that they observe or learn about in their professional capacity or in the context of their work and that involve a member of the University community or which occurred at a University-sponsored event or on University property. Please review the University Reporting Protocol.
A student can file a report here.
Confidential reporting for students
There are a number of resources on campus that can provide a confidential space where students can explore their options, talk about what happened, and obtain support services. Individuals often find it difficult to speak about what happened. Talking with someone once, or receiving ongoing support, can aid in recovery and assist with safety planning. If students access these services, they will be directed to other needed resources. These private and confidential resources are available at no cost. These services are not required to report incidents to the Office of Institutional Equity or campus police.
A student can access confidential resources here.
Mandatory reporting for faculty and staff
All University “responsible employees” and volunteers who are not otherwise exempted by this policy and/or applicable law must promptly report incidents of relationship violence, sexual misconduct, stalking, and retaliation that they observe or learn about in their professional capacity or in the context of their work and that involve a member of the University community or which occurred at a University-sponsored event or on University property. Please review the University Reporting Protocol.
Posted by: Kelly Mazurkiewicz
Justice and Belonging
Posted on: #iteachmsu
Optional Syllabus Statements: Inclusion
The following are a optional Inclusion Statements to include on your syllabus:
Michigan State University is committed to providing access and promoting/protecting freedom of speech in an inclusive learning environment. Discrimination and harassment based on a protected identity are prohibited. Please review MSU’s Notice of Non-Discrimination, Anti-Harassment, and Non-Retaliation.
In this class, we will work together to create and maintain a respectful teaching and learning environment where we engage in conversations that challenge our perspectives and understanding.
Please let me know if you would like me to use a name for you that is not reflected in the University system or if there is anything else I can do to support your access to this class.
Language that should NOT be included in a syllabus
Language that appears to promote protected identity-based preferences or otherwise violates federal or state civil rights laws
Language that appears to restrict First Amendment rights
References to any “policy” that is not a University or unit-level policy
Also, for your reference:Religious Observances & Holidays: Michigan State University has long had a policy to permit students, faculty/academic staff, and support staff to observe those holidays set aside by their chosen religious faith.
Links to the policies can be found below:
Religious Observance Policy (students, faculty, academic staff)
Support Staff Policy for Observance of Religious Holidays (support staff)
More information about religious holidays and traditions can be found online.
Interfaith Calendar
Center for Spiritual and Ethical Education
Ramadan at MSU
Provisional Land Acknowledgement: (This paragraph is intended to be read at the beginning of formal events or published in printed material.)
We collectively acknowledge that Michigan State University occupies the ancestral, traditional, and contemporary Lands of the Anishinaabeg – Three Fires Confederacy of Ojibwe, Odawa, and Potawatomi peoples. In particular, the University resides on Land ceded in the 1819 Treaty of Saginaw. We recognize, support, and advocate for the sovereignty of Michigan’s twelve federally-recognized Indian nations, for historic Indigenous communities in Michigan, for Indigenous individuals and communities who live here now, and for those who were forcibly removed from their Homelands. By offering this Land Acknowledgement, we affirm Indigenous sovereignty and will work to hold Michigan State University more accountable to the needs of American Indian and Indigenous peoples.Visit MSU's American Indian and Indigenous Studies page for more information on Land Acknowledgements.
Michigan State University is committed to providing access and promoting/protecting freedom of speech in an inclusive learning environment. Discrimination and harassment based on a protected identity are prohibited. Please review MSU’s Notice of Non-Discrimination, Anti-Harassment, and Non-Retaliation.
In this class, we will work together to create and maintain a respectful teaching and learning environment where we engage in conversations that challenge our perspectives and understanding.
Please let me know if you would like me to use a name for you that is not reflected in the University system or if there is anything else I can do to support your access to this class.
Language that should NOT be included in a syllabus
Language that appears to promote protected identity-based preferences or otherwise violates federal or state civil rights laws
Language that appears to restrict First Amendment rights
References to any “policy” that is not a University or unit-level policy
Also, for your reference:Religious Observances & Holidays: Michigan State University has long had a policy to permit students, faculty/academic staff, and support staff to observe those holidays set aside by their chosen religious faith.
Links to the policies can be found below:
Religious Observance Policy (students, faculty, academic staff)
Support Staff Policy for Observance of Religious Holidays (support staff)
More information about religious holidays and traditions can be found online.
Interfaith Calendar
Center for Spiritual and Ethical Education
Ramadan at MSU
Provisional Land Acknowledgement: (This paragraph is intended to be read at the beginning of formal events or published in printed material.)
We collectively acknowledge that Michigan State University occupies the ancestral, traditional, and contemporary Lands of the Anishinaabeg – Three Fires Confederacy of Ojibwe, Odawa, and Potawatomi peoples. In particular, the University resides on Land ceded in the 1819 Treaty of Saginaw. We recognize, support, and advocate for the sovereignty of Michigan’s twelve federally-recognized Indian nations, for historic Indigenous communities in Michigan, for Indigenous individuals and communities who live here now, and for those who were forcibly removed from their Homelands. By offering this Land Acknowledgement, we affirm Indigenous sovereignty and will work to hold Michigan State University more accountable to the needs of American Indian and Indigenous peoples.Visit MSU's American Indian and Indigenous Studies page for more information on Land Acknowledgements.
Posted by: Makena Neal
Navigating Context
Posted on: #iteachmsu
Who (and What) is Diversity Education For? Expanding Assessment Research on Anti-Racist Diversity Ed
Topic Area: DEI
Presented by: Patrick Arnold
Abstract:
Diversity education increasingly takes an anti-racist, anti-sexist, and trans-inclusive orientation, and aims to highlight the dynamics between power, privilege, and forms of oppression which permeate many of our institutions and create conditions of discrimination and marginalization. Extensive scholarship has emerged on the theoretical frameworks, teaching methods, and the impact of diversity education within settings like university courses or DEI (diversity, equity, and inclusion) programming. Educational and psychological research has studied anti-racist diversity education as a form of intervention: A central purpose of anti-racist education, after all, is to increase understanding of bias, and promote ways of ending systemic racial discrimination (Lynch, Swartz, & Isaacs, 2017). Naturally, then, it is common to evaluate the effectiveness of diversity education by measuring change in relevant attitudes, beliefs, or implicit biases of the participants of these interventions. However, diversity education is important not merely because it can be an intervention on existing bias, nor is the only appropriate audience for this context subjects who display such biases. In this pilot study, we explore more expansive data on the impact of diversity education, collected via a large intro course covering diversity in sex, gender, and current social justice issues like #BlackLivesMatter. Importantly, we find that diversity education is particularly impactful on the sense of belonging the students feel toward the university and its community, and especially for students of color enrolled in the course. We argue that further research is needed on diversity education as also an affirmation of belonging in our institutions.
Ingrid Lynch, Sharlene Swartz & Dane Isaacs (2017) Anti-racist moral education: A review of approaches, impact and theoretical underpinnings from 2000 to 2015, Journal of Moral Education, 46:2, 129-144, DOI: 10.1080/03057240.2016.1273825
Presented by: Patrick Arnold
Abstract:
Diversity education increasingly takes an anti-racist, anti-sexist, and trans-inclusive orientation, and aims to highlight the dynamics between power, privilege, and forms of oppression which permeate many of our institutions and create conditions of discrimination and marginalization. Extensive scholarship has emerged on the theoretical frameworks, teaching methods, and the impact of diversity education within settings like university courses or DEI (diversity, equity, and inclusion) programming. Educational and psychological research has studied anti-racist diversity education as a form of intervention: A central purpose of anti-racist education, after all, is to increase understanding of bias, and promote ways of ending systemic racial discrimination (Lynch, Swartz, & Isaacs, 2017). Naturally, then, it is common to evaluate the effectiveness of diversity education by measuring change in relevant attitudes, beliefs, or implicit biases of the participants of these interventions. However, diversity education is important not merely because it can be an intervention on existing bias, nor is the only appropriate audience for this context subjects who display such biases. In this pilot study, we explore more expansive data on the impact of diversity education, collected via a large intro course covering diversity in sex, gender, and current social justice issues like #BlackLivesMatter. Importantly, we find that diversity education is particularly impactful on the sense of belonging the students feel toward the university and its community, and especially for students of color enrolled in the course. We argue that further research is needed on diversity education as also an affirmation of belonging in our institutions.
Ingrid Lynch, Sharlene Swartz & Dane Isaacs (2017) Anti-racist moral education: A review of approaches, impact and theoretical underpinnings from 2000 to 2015, Journal of Moral Education, 46:2, 129-144, DOI: 10.1080/03057240.2016.1273825
Authored by: Patrick Arnold
Justice and Belonging
Posted on: #iteachmsu
Round Table to explore Trauma-Informed Student Engagement
Topic Area: Information Session
Presented By: Cheryl Williams-Hecksel
Abstract:
The Trauma Services and Training Network, formed in 2018, is comprised of representatives of academic and service units at MSU that are involved in providing trauma specific services and training. In the Fall of 2019, this focus expanded as a TSTN Faculty Learning Community was formed. The TSTN continues to convene members of the University community who are interested in and committed to creating a trauma informed institution. The work of TSTN has continued and takes on increasing significance as members of the University community negotiate the current pandemic as well as current issues related to racial disparities and discrimination.
The principals that a trauma informed institution embraces are Safety, Trustworthiness, Choice, Collaboration and Empowerment with ongoing attention to issues of Equity and Inclusion. A trauma informed organization promotes these principals as values that support assuring that all people are engaged in a manner that is sensitive to potential adverse and traumatic experiences. This roundtable discussion will engage participants in exploring strategies and challenges related to engagement of students through trauma informed teaching and service delivery.This roundtable provides an important opportunity for the TSTN to engage additional stakeholders in the current and future work of the faculty learning community.
Trauma Informed Teaching – Source List – May 2021
Carello, J., & Butler, L. D. (2015). Practicing what we teach: Trauma-informed educational practice. Journal of Teaching in Social Work, 35(3), 262-278.
Copeland, W. E., Keeler, G., Angold, A., & Costello, E. J. (2007). Traumatic events and posttraumatic stress in childhood. Archives of general psychiatry, 64(5), 577-584.
Davidson, S. (2017). Trauma-informed practices for postsecondary education: A guide. Retrieved October, 12, 2019.
Galatzer-Levy, I. R., Burton, C. L., & Bonanno, G. A. (2012). Coping flexibility, potentially traumatic life events, and resilience: A prospective study of college student adjustment. Journal of Social and Clinical Psychology, 31(6), 542-567.
Griffin, M. J., & Read, J. P. (2012). Prospective effects of method of coercion in sexual victimization across the first college year. Journal of interpersonal violence, 27(12), 2503-2524.
Kilpatrick, D. G., Ruggiero, K. J., Acierno, R., Saunders, B. E., Resnick, H. S., & Best, C. L. (2003). Violence and risk of PTSD, major depression, substance abuse/dependence, and comorbidity: results from the National Survey of Adolescents. Journal of consulting and clinical psychology, 71(4), 692.
Knight, C. (2010). Indirect trauma in the field practicum: Secondary traumatic stress, vicarious trauma, and compassion fatigue among social work students and their field instructors. Journal of Baccalaureate Social Work, 15(1), 31-52.
Michigan State University, Sexual Assault & Relationship Violence Training, Prevention, Outreach and Education Department. https://poe.msu.edu/programs/index.html ,2021.
Minahan, J. (2019). Trauma-informed teaching strategies. Educational Leadership, 77(2), 30-35.
O’Donnell, M. L., Creamer, M., & Pattison, P. (2004). Posttraumatic stress disorder and depression following trauma: understanding comorbidity. American Journal of Psychiatry, 161(8), 1390-1396.
Perkins, S., & Graham-Bermann, S. (2012). Violence exposure and the development of school-related functioning: Mental health, neurocognition, and learning. Aggression and violent behavior, 17(1), 89-98.
Read, J. P., Ouimette, P., White, J., Colder, C., & Farrow, S. (2011). Rates of DSM–IV–TR trauma exposure and posttraumatic stress disorder among newly matriculated college students. Psychological Trauma: Theory, Research, Practice, and Policy, 3(2), 148.
Rodenbush, K. (2015). The effects of trauma on behavior in the classroom [Presentation materials]. Retrieved from Monterey County, Office of Education website: http://www. montereycoe. org/Assets/selpa/Files/Presentation-Materials/The% 20Effects, 20, 299-309
Rytwinski, N. K., Scur, M. D., Feeny, N. C., & Youngstrom, E. A. (2013). The co‐occurrence of major depressive disorder among individuals with posttraumatic stress disorder: A meta‐analysis. Journal of traumatic stress, 26(3), 299-309.
Smyth, J. M., Hockemeyer, J. R., Heron, K. E., Wonderlich, S. A., & Pennebaker, J. W. (2008). Prevalence, type, disclosure, and severity of adverse life events in college students. Journal of American College Health, 57(1), 69-76.
Substance Abuse and Mental Health Services Administration. SAMHSA’s Concept of Trauma and Guidance for a Trauma-Informed Approach. HHS Publication No. (SMA) 14-4884. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2014.
University of Buffalo School of Social Work (January 2020) Trauma-Informed Organizational Change Manual. The Institute on Trauma and Trauma-Informed Care, https://socialwork.buffalo.edu/ittic
Presented By: Cheryl Williams-Hecksel
Abstract:
The Trauma Services and Training Network, formed in 2018, is comprised of representatives of academic and service units at MSU that are involved in providing trauma specific services and training. In the Fall of 2019, this focus expanded as a TSTN Faculty Learning Community was formed. The TSTN continues to convene members of the University community who are interested in and committed to creating a trauma informed institution. The work of TSTN has continued and takes on increasing significance as members of the University community negotiate the current pandemic as well as current issues related to racial disparities and discrimination.
The principals that a trauma informed institution embraces are Safety, Trustworthiness, Choice, Collaboration and Empowerment with ongoing attention to issues of Equity and Inclusion. A trauma informed organization promotes these principals as values that support assuring that all people are engaged in a manner that is sensitive to potential adverse and traumatic experiences. This roundtable discussion will engage participants in exploring strategies and challenges related to engagement of students through trauma informed teaching and service delivery.This roundtable provides an important opportunity for the TSTN to engage additional stakeholders in the current and future work of the faculty learning community.
Trauma Informed Teaching – Source List – May 2021
Carello, J., & Butler, L. D. (2015). Practicing what we teach: Trauma-informed educational practice. Journal of Teaching in Social Work, 35(3), 262-278.
Copeland, W. E., Keeler, G., Angold, A., & Costello, E. J. (2007). Traumatic events and posttraumatic stress in childhood. Archives of general psychiatry, 64(5), 577-584.
Davidson, S. (2017). Trauma-informed practices for postsecondary education: A guide. Retrieved October, 12, 2019.
Galatzer-Levy, I. R., Burton, C. L., & Bonanno, G. A. (2012). Coping flexibility, potentially traumatic life events, and resilience: A prospective study of college student adjustment. Journal of Social and Clinical Psychology, 31(6), 542-567.
Griffin, M. J., & Read, J. P. (2012). Prospective effects of method of coercion in sexual victimization across the first college year. Journal of interpersonal violence, 27(12), 2503-2524.
Kilpatrick, D. G., Ruggiero, K. J., Acierno, R., Saunders, B. E., Resnick, H. S., & Best, C. L. (2003). Violence and risk of PTSD, major depression, substance abuse/dependence, and comorbidity: results from the National Survey of Adolescents. Journal of consulting and clinical psychology, 71(4), 692.
Knight, C. (2010). Indirect trauma in the field practicum: Secondary traumatic stress, vicarious trauma, and compassion fatigue among social work students and their field instructors. Journal of Baccalaureate Social Work, 15(1), 31-52.
Michigan State University, Sexual Assault & Relationship Violence Training, Prevention, Outreach and Education Department. https://poe.msu.edu/programs/index.html ,2021.
Minahan, J. (2019). Trauma-informed teaching strategies. Educational Leadership, 77(2), 30-35.
O’Donnell, M. L., Creamer, M., & Pattison, P. (2004). Posttraumatic stress disorder and depression following trauma: understanding comorbidity. American Journal of Psychiatry, 161(8), 1390-1396.
Perkins, S., & Graham-Bermann, S. (2012). Violence exposure and the development of school-related functioning: Mental health, neurocognition, and learning. Aggression and violent behavior, 17(1), 89-98.
Read, J. P., Ouimette, P., White, J., Colder, C., & Farrow, S. (2011). Rates of DSM–IV–TR trauma exposure and posttraumatic stress disorder among newly matriculated college students. Psychological Trauma: Theory, Research, Practice, and Policy, 3(2), 148.
Rodenbush, K. (2015). The effects of trauma on behavior in the classroom [Presentation materials]. Retrieved from Monterey County, Office of Education website: http://www. montereycoe. org/Assets/selpa/Files/Presentation-Materials/The% 20Effects, 20, 299-309
Rytwinski, N. K., Scur, M. D., Feeny, N. C., & Youngstrom, E. A. (2013). The co‐occurrence of major depressive disorder among individuals with posttraumatic stress disorder: A meta‐analysis. Journal of traumatic stress, 26(3), 299-309.
Smyth, J. M., Hockemeyer, J. R., Heron, K. E., Wonderlich, S. A., & Pennebaker, J. W. (2008). Prevalence, type, disclosure, and severity of adverse life events in college students. Journal of American College Health, 57(1), 69-76.
Substance Abuse and Mental Health Services Administration. SAMHSA’s Concept of Trauma and Guidance for a Trauma-Informed Approach. HHS Publication No. (SMA) 14-4884. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2014.
University of Buffalo School of Social Work (January 2020) Trauma-Informed Organizational Change Manual. The Institute on Trauma and Trauma-Informed Care, https://socialwork.buffalo.edu/ittic
Authored by: Cheryl Williams-Hecksel
Pedagogical Design
Posted on: Center for Teaching...
Centering Intersectionality in Inclusive Pedagogy
This post provides an overview of intersectionality as part of the Inclusive Pedagogy playlist.
Intersectionality acknowledges that folks’ identities are multi-faceted and interconnected, influencing their experiences and interactions. Intersectionality is a framework to consider the ways that groups and individuals have unique combinations of privilege and discrimination. Within this, society has interlocking and overlapping systems of oppression. These systems create our institutions, which include education, banking, criminal justice and law, state welfare, media, housing, etc. (Kendall). Then, each of these systems not only interlock and overlap, but they create obstacles, harm, and oppression for anyone who does not have societally privileged identities (white, straight, cisgender, abled-bodied and able-minded, high socioeconomic status, thin body size, etc.). All identities (e.g., race, nationality, language use, gender, sexuality, religion, class, immigration status, trauma survivorship, etc.) are contextually specific to a place and time. These identities cannot be separated at that individual level. For instance, Crenshaw discusses how intersectionality helps to “account for multiple grounds of identity when considering how the social world is constructed” (1245). In other words, each identity interplays with one another to where they can’t be disentangled, such as a Black woman’s experiences may be an interplay of racism and sexism called misogynoir.
In considering these identity and institutional dimensions, there are many visual iterations of identities (Cabiness-Atkinson). The Northcentral University Diversity Wheel illustrates the various components of identity that are personal to self, such as gender, age, race, etc., to those that are developed by social influences and life as well as how that is affected by positionalities within institutions.
As educators, we must consider our own intersectional identities and how those interact with the systems of oppression and its institutions. To model this inclusive and intersectional pedagogy, it is recommended to (revised and adapted from Case 9):
Reflect and unpack on your own identities and biases and how that may “alter lived experiences of prejudice and discrimination, privilege and opportunities, and perspectives from particular social locations.” One way is to attend MSU’s Implicit Bias Certification course. Another avenue to reflect and unpack would be to engage with the University of Illinois' compilation of activities to raise awareness of biases.
Continue to unlearn and learn and continually strive to learn more about identities, privilege, and inclusive pedagogy. Some initial and/or continuing resources include Boston University’s Self-Guided Diversity and Inclusion Learning Toolkits.
Foster learner reflection and agency for their own un/learning. Some strategies for this are included later in this series’ Classroom Activities article.
Incorporate diverse social identities typically neglected in course curriculum, interdisciplinary ways of thinking, multiple pathways for learners, and an asset-based approach for thinking about learners.
In addition to the above, the next articles will continue to offer ways to become more inclusive and intersectional in education.
Continue to read more about inclusive pedagogy in the next article, “Unpacking Problematic Language” or return to the Inclusive Pedagogy playlist.
Intersectionality acknowledges that folks’ identities are multi-faceted and interconnected, influencing their experiences and interactions. Intersectionality is a framework to consider the ways that groups and individuals have unique combinations of privilege and discrimination. Within this, society has interlocking and overlapping systems of oppression. These systems create our institutions, which include education, banking, criminal justice and law, state welfare, media, housing, etc. (Kendall). Then, each of these systems not only interlock and overlap, but they create obstacles, harm, and oppression for anyone who does not have societally privileged identities (white, straight, cisgender, abled-bodied and able-minded, high socioeconomic status, thin body size, etc.). All identities (e.g., race, nationality, language use, gender, sexuality, religion, class, immigration status, trauma survivorship, etc.) are contextually specific to a place and time. These identities cannot be separated at that individual level. For instance, Crenshaw discusses how intersectionality helps to “account for multiple grounds of identity when considering how the social world is constructed” (1245). In other words, each identity interplays with one another to where they can’t be disentangled, such as a Black woman’s experiences may be an interplay of racism and sexism called misogynoir.
In considering these identity and institutional dimensions, there are many visual iterations of identities (Cabiness-Atkinson). The Northcentral University Diversity Wheel illustrates the various components of identity that are personal to self, such as gender, age, race, etc., to those that are developed by social influences and life as well as how that is affected by positionalities within institutions.
As educators, we must consider our own intersectional identities and how those interact with the systems of oppression and its institutions. To model this inclusive and intersectional pedagogy, it is recommended to (revised and adapted from Case 9):
Reflect and unpack on your own identities and biases and how that may “alter lived experiences of prejudice and discrimination, privilege and opportunities, and perspectives from particular social locations.” One way is to attend MSU’s Implicit Bias Certification course. Another avenue to reflect and unpack would be to engage with the University of Illinois' compilation of activities to raise awareness of biases.
Continue to unlearn and learn and continually strive to learn more about identities, privilege, and inclusive pedagogy. Some initial and/or continuing resources include Boston University’s Self-Guided Diversity and Inclusion Learning Toolkits.
Foster learner reflection and agency for their own un/learning. Some strategies for this are included later in this series’ Classroom Activities article.
Incorporate diverse social identities typically neglected in course curriculum, interdisciplinary ways of thinking, multiple pathways for learners, and an asset-based approach for thinking about learners.
In addition to the above, the next articles will continue to offer ways to become more inclusive and intersectional in education.
Continue to read more about inclusive pedagogy in the next article, “Unpacking Problematic Language” or return to the Inclusive Pedagogy playlist.
Authored by: Bethany Meadows
Justice and Belonging
Posted on: GenAI & Education
Artificial Intelligence in Higher Education (and Learning)
The following are a collection of publicly sourced articles related to the recent rise of artificial intelligence in everyday applications.
note: following each [hyperlinked] title/subtitle are abstracts generated by ChatGPT after receiving prompts from M. Neal. "Write an abstract for [article link]" is indicated with [URL] abstract. "Write an abstract for [article text]" is indicated with [text] abstract. These very similar prompt-responses are shared consecutively in the hope that reading the abstracts will showcase the variations in ChatGPT output (despite similar input).
Deconstructing ChatGPT on the Future of Continuing Education
The future has arrived in continuing education—however, many have yet to realize the arrival.
[URL] Abstract: "The rise of AI technology and advancements in language models, such as ChatGPT, are poised to change the face of continuing education. The technology offers the potential for personalized and interactive learning experiences, making education more accessible and convenient for students. However, there are concerns about the potential job displacement and ethical implications of relying heavily on AI-powered learning systems. The article explores the potential benefits and drawbacks of ChatGPT and other AI systems in continuing education, and the need for careful consideration of these implications as the technology continues to evolve."
[text] Abstract: The recently released ChatGPT and GPT-3.5 from OpenAI have the potential to revolutionize the field of education. The advancements in AI technology will support heutagogy, which emphasizes student-centered, self-determined learning. AI will serve as a learning assistant, providing personalized and adaptive paths for learners. The technology promises universal access to education and a brighter future for lifelong learning. OpenAI has also taken steps to protect the system from providing harmful content, using a combination of a special prompt and Reinforcement Learning from Human Feedback (RLHF). Early user responses have been positive, with some stating that ChatGPT could potentially replace human-written essays.
ChatGPT and the rise of AI writers: how should higher education respond?
The proliferation of AI text generators such as ChatGPT has major implications for higher education. Nancy Gleason explores how educators should respond to these tools which can write essays in seconds
[URL] Abstract: "The rise of AI language models like ChatGPT is having a significant impact on writing and journalism, and higher education must respond. As AI technology continues to improve and become more prevalent, it is likely to impact the skills and knowledge required of future writers and journalists. Higher education institutions must consider how to adapt and prepare students for a future where AI-generated writing is increasingly common. The article argues that higher education institutions must play a role in preparing students for the ethical and practical implications of working with AI systems and in shaping the future of writing and journalism in an age of AI."
[text] Abstract: The article discusses the latest developments in deep machine learning, specifically the highly sophisticated AI chatbot ChatGPT developed by OpenAI. The author notes that the new interface has attracted over a million users in just five days and that ChatGPT is free and can generate text in various structured languages. The author also acknowledges potential concerns, such as the accuracy and bias of AI-generated text, but argues that these are dynamic and improving. The author argues that higher education institutions need to embrace the use of AI-generated text, but also need to reassess their pedagogical and assessment practices to incorporate AI-generated text in a way that aligns with the goals of equity, inclusion, and access. The author suggests that assessment should focus on process rather than outcome and gives a sample class activity that encourages students to compare assigned readings with AI-generated content.
Chatgpt And Its Effects On Higher Education (Full article written by ChatGPT)
[URL] Abstract: The use of ChatGPT in higher education has both benefits and drawbacks. ChatGPT is a natural language processing model that can generate human-like text responses to input text, and is trained on large amounts of text data to learn the patterns and structures of human language. This makes it useful for enhancing language understanding, improving writing skills, and increasing accessibility for students with disabilities. However, NLP models can also reproduce and amplify biases and discrimination in the data they are trained on, have limited flexibility, and create a dependence on technology. Cheating on exams with NLP models is also possible and difficult to prevent, but strict monitoring and oversight can help mitigate this risk.
How ChatGPT Could Transform Higher Education
[URL] abstract: This article discusses the potential impact of OpenAI's language model, ChatGPT, on higher education. It highlights the ability of ChatGPT to provide personalized and automated answers to students' questions, allowing for more efficient and accessible education. The article also touches on the potential ethical considerations and the need for proper implementation and regulation in order to maximize the benefits and minimize potential negative consequences.
[text] abstract: ChatGPT is a large language model developed by OpenAI that excels in various text-based tasks, such as writing and composing. In the field of higher education, ChatGPT has the potential to revolutionize the way students and educators approach learning by providing personalized real-time responses to questions and needs. However, there are also significant dangers associated with the use of ChatGPT in higher education, including the potential for the model to reproduce biases and stereotypes and to reduce human interaction and personalized feedback in the learning process.
Freaking Out About ChatGPT—Part I
Artificial intelligence can crank out passable student essays in seconds. What are we going to do?
[text] article: The OpenAI ChatGPT interface has raised concerns in the academic community due to its ability to produce high-quality writing in seconds. The author, who has been monitoring the technology, finds the progress of GPT3 remarkable but also sees it as an opportunity to re-examine teaching practices and align them with pedagogical values. ChatGPT, however, has no understanding of content and cannot synthesize or evaluate information accurately. The author fed ChatGPT sample questions from past AP exams and was surprised by the quality of the responses. The author argues that the prevalence of standardized assessments and templates like the five-paragraph essay has corrupted the learning process and affected student writing abilities and attitudes towards writing and school. To address this, the author suggests providing students with learning experiences of intrinsic interest, utilizing methods of assessment that consider the learning process, and requiring students to demonstrate understanding in different ways.
[URL] abstract: The article "Freaking Out About ChatGPT- Part I" discusses the potential ethical and societal implications of OpenAI's language model, ChatGPT. The author highlights the concerns of chatbots being used for malicious purposes and the consequences of having AI models with advanced language capabilities. The article suggests that as AI technology continues to advance, it is crucial to consider the ethical implications and take steps to mitigate potential negative consequences.
Using Artificial Intelligence in the Classroom
[URL] abstract: This guide provides an overview of using artificial intelligence (AI) in the classroom. It discusses the benefits and challenges of incorporating AI technologies, such as chatbots and machine learning algorithms, into education. It also explores various examples of AI applications in education, such as personalized learning and language tutoring. The guide also provides recommendations for educators and institutions looking to integrate AI into their teaching practices.
[text] Abstract: ChatGPT, a new conversational artificial intelligence (AI) program, has sparked discussions on its potential impact on higher education and the workforce. While some fear its threat, instructors can use it as an opportunity to educate students on AI by incorporating it in their teaching methods. This approach can encourage student participation in a larger societal discussion, help them develop ethical grounding and understanding of academic integrity related to AI. To prepare, instructors should reflect on the potential threats and benefits, test AI themselves, revise assignments, consider data and privacy policies, and identify and communicate opportunities in their course.
4 Ways Universities Can Use AI to Streamline Operations
[URL] Abstract: Artificial intelligence (AI) is increasingly being adopted by universities to streamline their operations and improve the student experience. AI can help universities save time and resources by automating repetitive tasks, such as scheduling, student services, and administrative functions. There are several ways that universities can use AI to streamline operations and improve efficiency.
Personalized Student Services: AI can be used to provide students with personalized support and information, including admission and enrollment guidance, financial aid, and course scheduling.
Improved Admissions Process: AI can automate the time-consuming and repetitive task of reviewing and sorting through large numbers of applications, enabling universities to process applications faster and more efficiently.
Streamlined Administrative Functions: AI can automate routine tasks, such as student registration, grade reporting, and course scheduling, freeing up staff time and resources for more important tasks.
Enhance Student Learning: AI can be integrated into the curriculum, providing students with customized and interactive learning experiences that can improve their comprehension and retention of course material.
In conclusion, AI has the potential to revolutionize the way universities operate, improving efficiency and the student experience. Universities can use AI to streamline operations, save time and resources, and improve the overall educational experience.
[text] Abstract: This article explains the benefits of using AI chatbots in higher education institutions. AI chatbots can help reduce call and email volume, streamline the application process, increase availability and accessibility for students, and improve operational efficiency for staff. For example, chatbots can answer routine questions from students 24/7 and remind students about unfinished applications. This can increase the likelihood of students enrolling, leading to better margins for the institution. By improving operational efficiency, staff can focus on more complex interactions with students. Chatbots have already been successful in reducing costs for universities and colleges.
ChatGPT: A Must-See Before the Semester Begins
[URL] Abstract: The article "ChatGPT: A Must-See Before the Semester Begins" focuses on the application of advanced language model technology in the classroom. It highlights the potential benefits of using OpenAI's ChatGPT for educational purposes, including improved student engagement and increased efficiency in answering frequently asked questions. The article also provides tips for integrating ChatGPT into teaching practices, such as using it for language translation and enhancing discussion forums. Overall, the article emphasizes the importance of utilizing cutting-edge technology in education and presents ChatGPT as a valuable tool for educators.
[text] Abstract: This article discusses the potential impact of AI in education, specifically in the realm of writing. The author highlights the capabilities of a language model called ChatGPT, which is capable of generating various forms of writing including movie scripts, sonnets, grant proposals, and more. The author argues that the advent of AI writing technology could potentially lead to a shift in the way education is approached, moving away from traditional rote learning and towards a model that emphasizes student-driven learning and collaboration with AI. The author also raises questions about the ethical implications of AI writing, and encourages educators to consider the possibilities for creating more meaningful and purposeful learning experiences for students.
How Emotion AI will change the online learning landscape
[URL] Abstract: Emotion AI is a rapidly developing field that uses artificial intelligence to recognize and respond to human emotions. This technology has the potential to revolutionize the online learning landscape by creating a more personalized and engaging learning experience. By using Emotion AI, online learning platforms can track and respond to the emotional state of students, making the learning process more adaptive and effective. This article explores the benefits of Emotion AI in online learning and how it will shape the future of education.
[text] Abstract: Emotion AI, a branch of affective computing, is gaining mainstream attention for its ability to recognize and respond to human emotions. With the growth of technology, understanding both the cognitive and affective channels of human connection is crucial. As such, industries such as automotive, retail, and education are investing in making their technology more human-like using computer vision and speech recognition. In the education sector, Emotion AI is expected to transform online learning by providing a more personalized and engaging experience for learners. By monitoring the emotions of students and providing feedback to instructors, Emotion AI can improve the learning process and tailor the curriculum to each student's needs. The technology has the potential to play an increasingly important role in the online learning landscape and is likely to transform the way we learn in the future.
ChatGPT Advice Academics Can Use Now
To harness the potential and avert the risks of OpenAI’s new chat bot, academics should think a few years out, invite students into the conversation and—most of all—experiment, not panic.
[URL] Abstract: This article reports on advice offered by academic experts on how to use AI language models like ChatGPT in academia. The experts discuss the benefits and limitations of using AI language models, and offer suggestions on how to effectively integrate them into research and teaching. They also emphasize the importance of being aware of ethical considerations, such as ensuring the appropriate use of data and avoiding the spread of misinformation. The article provides valuable insights for academic institutions looking to utilize AI language models in their work.
[text] Abstract: With the advent of ChatGPT, a language model released by OpenAI, the academic community is grappling with the potential and risks posed by this game-changing technology. The bot writes essays, poems, and debates on a wide range of topics and has even earned passing scores on the bar exam. While some see opportunities for accelerating discussions about teaching and learning, others worry about widespread cheating. Experts in higher education suggest a deliberate and flexible approach to ChatGPT. Faculty members should familiarize themselves with AI writing aids and consider their implications for different courses. Administrators should support faculty training and provide clear instructions to students on the use of AI aids. The focus should be on how these tools can achieve learning outcomes and promote equity and access. By thinking a few years ahead and asking the right questions, academic integrity concerns can be minimized while promoting learning outcomes.
Thoughts about the impact of AI text on assessment
[URL] Abstract: The article "Thoughts About the Impact of AI on Text Assessment" explores the potential consequences of the widespread adoption of artificial intelligence in the field of text assessment. The author discusses the various advantages and disadvantages of relying on AI algorithms, including the ability to analyze large amounts of data quickly, the potential for unbiased scoring, and the possibility of oversimplifying complex linguistic phenomena. They also examine the ethical considerations involved in using AI for text assessment, such as accountability, privacy, and the potential for AI to perpetuate existing biases. Overall, the article provides a comprehensive overview of the impact of AI on text assessment and encourages readers to consider both the benefits and challenges of this technology.
[text] Abstract: The use of Large Language Models (LLMs) like ChatGPT has raised concerns in the education community regarding their impact on assessment. The author highlights that AI-generated text is not a new problem, as similar issues exist with the use of search engines and essay-writing services. The truthfulness and trustworthiness of AI-generated text are not exclusive to AI, as people can also write untruthful information. The author suggests that the solution to assessment is not to rely on large texts or quizzes, but to focus on long-term engagement for building reputation. The education system needs to be restructured to keep small class sizes and emphasize 1:1 engagement for quality learning. The author also points out that AIs will play a significant role in our lives and need to be educated to be friendly and not competition.
ADDITIONAL RESOURCES
How to Productively Address AI-Generated Text in Your Classroom
What are ChatGPT and AI-generated text?
How can you most productively address Chat-GPT and other AI text tools?
Why might students use AI-generated text?
How can you identify AI-generated text?
How can you address AI-generated content in your syllabus and course design?
How can you adjust assignments to make them more AI-resistant?
How can you embrace the AI tools for improving student learning?
ChatGPT and AI in Higher Education: Opportunities and Challenges
Presenters: Vivek Astvansh, Paul Cook, Jeanette Heidewald, Rebecca Itow, Kevin Jones
Moderator: Adam Maksl
Recorded Wednesday, January 18, 2023 3 - 4 p.m. EST
A panel of faculty and experts across IU campuses explores the potential uses and challenges of ChatGPT and other AI technologies in teaching and learning. We've seen many media reports in recent weeks about the technology. Discussions have included not only concerns about students using the tool to cheat but also opportunities to use such tech in automating administrative tasks or proactively introducing students to technology likely to shape the future of work.
In this webinar, we provided a brief overview of the technology and explored these topics and more, identifying both challenges and opportunities for teaching and learning. Our panelists provided diverse, cross-disciplinary perspectives. This panel was the first in a series of programs offered across IU campuses on AI and its role in teaching and learning.
note: following each [hyperlinked] title/subtitle are abstracts generated by ChatGPT after receiving prompts from M. Neal. "Write an abstract for [article link]" is indicated with [URL] abstract. "Write an abstract for [article text]" is indicated with [text] abstract. These very similar prompt-responses are shared consecutively in the hope that reading the abstracts will showcase the variations in ChatGPT output (despite similar input).
Deconstructing ChatGPT on the Future of Continuing Education
The future has arrived in continuing education—however, many have yet to realize the arrival.
[URL] Abstract: "The rise of AI technology and advancements in language models, such as ChatGPT, are poised to change the face of continuing education. The technology offers the potential for personalized and interactive learning experiences, making education more accessible and convenient for students. However, there are concerns about the potential job displacement and ethical implications of relying heavily on AI-powered learning systems. The article explores the potential benefits and drawbacks of ChatGPT and other AI systems in continuing education, and the need for careful consideration of these implications as the technology continues to evolve."
[text] Abstract: The recently released ChatGPT and GPT-3.5 from OpenAI have the potential to revolutionize the field of education. The advancements in AI technology will support heutagogy, which emphasizes student-centered, self-determined learning. AI will serve as a learning assistant, providing personalized and adaptive paths for learners. The technology promises universal access to education and a brighter future for lifelong learning. OpenAI has also taken steps to protect the system from providing harmful content, using a combination of a special prompt and Reinforcement Learning from Human Feedback (RLHF). Early user responses have been positive, with some stating that ChatGPT could potentially replace human-written essays.
ChatGPT and the rise of AI writers: how should higher education respond?
The proliferation of AI text generators such as ChatGPT has major implications for higher education. Nancy Gleason explores how educators should respond to these tools which can write essays in seconds
[URL] Abstract: "The rise of AI language models like ChatGPT is having a significant impact on writing and journalism, and higher education must respond. As AI technology continues to improve and become more prevalent, it is likely to impact the skills and knowledge required of future writers and journalists. Higher education institutions must consider how to adapt and prepare students for a future where AI-generated writing is increasingly common. The article argues that higher education institutions must play a role in preparing students for the ethical and practical implications of working with AI systems and in shaping the future of writing and journalism in an age of AI."
[text] Abstract: The article discusses the latest developments in deep machine learning, specifically the highly sophisticated AI chatbot ChatGPT developed by OpenAI. The author notes that the new interface has attracted over a million users in just five days and that ChatGPT is free and can generate text in various structured languages. The author also acknowledges potential concerns, such as the accuracy and bias of AI-generated text, but argues that these are dynamic and improving. The author argues that higher education institutions need to embrace the use of AI-generated text, but also need to reassess their pedagogical and assessment practices to incorporate AI-generated text in a way that aligns with the goals of equity, inclusion, and access. The author suggests that assessment should focus on process rather than outcome and gives a sample class activity that encourages students to compare assigned readings with AI-generated content.
Chatgpt And Its Effects On Higher Education (Full article written by ChatGPT)
[URL] Abstract: The use of ChatGPT in higher education has both benefits and drawbacks. ChatGPT is a natural language processing model that can generate human-like text responses to input text, and is trained on large amounts of text data to learn the patterns and structures of human language. This makes it useful for enhancing language understanding, improving writing skills, and increasing accessibility for students with disabilities. However, NLP models can also reproduce and amplify biases and discrimination in the data they are trained on, have limited flexibility, and create a dependence on technology. Cheating on exams with NLP models is also possible and difficult to prevent, but strict monitoring and oversight can help mitigate this risk.
How ChatGPT Could Transform Higher Education
[URL] abstract: This article discusses the potential impact of OpenAI's language model, ChatGPT, on higher education. It highlights the ability of ChatGPT to provide personalized and automated answers to students' questions, allowing for more efficient and accessible education. The article also touches on the potential ethical considerations and the need for proper implementation and regulation in order to maximize the benefits and minimize potential negative consequences.
[text] abstract: ChatGPT is a large language model developed by OpenAI that excels in various text-based tasks, such as writing and composing. In the field of higher education, ChatGPT has the potential to revolutionize the way students and educators approach learning by providing personalized real-time responses to questions and needs. However, there are also significant dangers associated with the use of ChatGPT in higher education, including the potential for the model to reproduce biases and stereotypes and to reduce human interaction and personalized feedback in the learning process.
Freaking Out About ChatGPT—Part I
Artificial intelligence can crank out passable student essays in seconds. What are we going to do?
[text] article: The OpenAI ChatGPT interface has raised concerns in the academic community due to its ability to produce high-quality writing in seconds. The author, who has been monitoring the technology, finds the progress of GPT3 remarkable but also sees it as an opportunity to re-examine teaching practices and align them with pedagogical values. ChatGPT, however, has no understanding of content and cannot synthesize or evaluate information accurately. The author fed ChatGPT sample questions from past AP exams and was surprised by the quality of the responses. The author argues that the prevalence of standardized assessments and templates like the five-paragraph essay has corrupted the learning process and affected student writing abilities and attitudes towards writing and school. To address this, the author suggests providing students with learning experiences of intrinsic interest, utilizing methods of assessment that consider the learning process, and requiring students to demonstrate understanding in different ways.
[URL] abstract: The article "Freaking Out About ChatGPT- Part I" discusses the potential ethical and societal implications of OpenAI's language model, ChatGPT. The author highlights the concerns of chatbots being used for malicious purposes and the consequences of having AI models with advanced language capabilities. The article suggests that as AI technology continues to advance, it is crucial to consider the ethical implications and take steps to mitigate potential negative consequences.
Using Artificial Intelligence in the Classroom
[URL] abstract: This guide provides an overview of using artificial intelligence (AI) in the classroom. It discusses the benefits and challenges of incorporating AI technologies, such as chatbots and machine learning algorithms, into education. It also explores various examples of AI applications in education, such as personalized learning and language tutoring. The guide also provides recommendations for educators and institutions looking to integrate AI into their teaching practices.
[text] Abstract: ChatGPT, a new conversational artificial intelligence (AI) program, has sparked discussions on its potential impact on higher education and the workforce. While some fear its threat, instructors can use it as an opportunity to educate students on AI by incorporating it in their teaching methods. This approach can encourage student participation in a larger societal discussion, help them develop ethical grounding and understanding of academic integrity related to AI. To prepare, instructors should reflect on the potential threats and benefits, test AI themselves, revise assignments, consider data and privacy policies, and identify and communicate opportunities in their course.
4 Ways Universities Can Use AI to Streamline Operations
[URL] Abstract: Artificial intelligence (AI) is increasingly being adopted by universities to streamline their operations and improve the student experience. AI can help universities save time and resources by automating repetitive tasks, such as scheduling, student services, and administrative functions. There are several ways that universities can use AI to streamline operations and improve efficiency.
Personalized Student Services: AI can be used to provide students with personalized support and information, including admission and enrollment guidance, financial aid, and course scheduling.
Improved Admissions Process: AI can automate the time-consuming and repetitive task of reviewing and sorting through large numbers of applications, enabling universities to process applications faster and more efficiently.
Streamlined Administrative Functions: AI can automate routine tasks, such as student registration, grade reporting, and course scheduling, freeing up staff time and resources for more important tasks.
Enhance Student Learning: AI can be integrated into the curriculum, providing students with customized and interactive learning experiences that can improve their comprehension and retention of course material.
In conclusion, AI has the potential to revolutionize the way universities operate, improving efficiency and the student experience. Universities can use AI to streamline operations, save time and resources, and improve the overall educational experience.
[text] Abstract: This article explains the benefits of using AI chatbots in higher education institutions. AI chatbots can help reduce call and email volume, streamline the application process, increase availability and accessibility for students, and improve operational efficiency for staff. For example, chatbots can answer routine questions from students 24/7 and remind students about unfinished applications. This can increase the likelihood of students enrolling, leading to better margins for the institution. By improving operational efficiency, staff can focus on more complex interactions with students. Chatbots have already been successful in reducing costs for universities and colleges.
ChatGPT: A Must-See Before the Semester Begins
[URL] Abstract: The article "ChatGPT: A Must-See Before the Semester Begins" focuses on the application of advanced language model technology in the classroom. It highlights the potential benefits of using OpenAI's ChatGPT for educational purposes, including improved student engagement and increased efficiency in answering frequently asked questions. The article also provides tips for integrating ChatGPT into teaching practices, such as using it for language translation and enhancing discussion forums. Overall, the article emphasizes the importance of utilizing cutting-edge technology in education and presents ChatGPT as a valuable tool for educators.
[text] Abstract: This article discusses the potential impact of AI in education, specifically in the realm of writing. The author highlights the capabilities of a language model called ChatGPT, which is capable of generating various forms of writing including movie scripts, sonnets, grant proposals, and more. The author argues that the advent of AI writing technology could potentially lead to a shift in the way education is approached, moving away from traditional rote learning and towards a model that emphasizes student-driven learning and collaboration with AI. The author also raises questions about the ethical implications of AI writing, and encourages educators to consider the possibilities for creating more meaningful and purposeful learning experiences for students.
How Emotion AI will change the online learning landscape
[URL] Abstract: Emotion AI is a rapidly developing field that uses artificial intelligence to recognize and respond to human emotions. This technology has the potential to revolutionize the online learning landscape by creating a more personalized and engaging learning experience. By using Emotion AI, online learning platforms can track and respond to the emotional state of students, making the learning process more adaptive and effective. This article explores the benefits of Emotion AI in online learning and how it will shape the future of education.
[text] Abstract: Emotion AI, a branch of affective computing, is gaining mainstream attention for its ability to recognize and respond to human emotions. With the growth of technology, understanding both the cognitive and affective channels of human connection is crucial. As such, industries such as automotive, retail, and education are investing in making their technology more human-like using computer vision and speech recognition. In the education sector, Emotion AI is expected to transform online learning by providing a more personalized and engaging experience for learners. By monitoring the emotions of students and providing feedback to instructors, Emotion AI can improve the learning process and tailor the curriculum to each student's needs. The technology has the potential to play an increasingly important role in the online learning landscape and is likely to transform the way we learn in the future.
ChatGPT Advice Academics Can Use Now
To harness the potential and avert the risks of OpenAI’s new chat bot, academics should think a few years out, invite students into the conversation and—most of all—experiment, not panic.
[URL] Abstract: This article reports on advice offered by academic experts on how to use AI language models like ChatGPT in academia. The experts discuss the benefits and limitations of using AI language models, and offer suggestions on how to effectively integrate them into research and teaching. They also emphasize the importance of being aware of ethical considerations, such as ensuring the appropriate use of data and avoiding the spread of misinformation. The article provides valuable insights for academic institutions looking to utilize AI language models in their work.
[text] Abstract: With the advent of ChatGPT, a language model released by OpenAI, the academic community is grappling with the potential and risks posed by this game-changing technology. The bot writes essays, poems, and debates on a wide range of topics and has even earned passing scores on the bar exam. While some see opportunities for accelerating discussions about teaching and learning, others worry about widespread cheating. Experts in higher education suggest a deliberate and flexible approach to ChatGPT. Faculty members should familiarize themselves with AI writing aids and consider their implications for different courses. Administrators should support faculty training and provide clear instructions to students on the use of AI aids. The focus should be on how these tools can achieve learning outcomes and promote equity and access. By thinking a few years ahead and asking the right questions, academic integrity concerns can be minimized while promoting learning outcomes.
Thoughts about the impact of AI text on assessment
[URL] Abstract: The article "Thoughts About the Impact of AI on Text Assessment" explores the potential consequences of the widespread adoption of artificial intelligence in the field of text assessment. The author discusses the various advantages and disadvantages of relying on AI algorithms, including the ability to analyze large amounts of data quickly, the potential for unbiased scoring, and the possibility of oversimplifying complex linguistic phenomena. They also examine the ethical considerations involved in using AI for text assessment, such as accountability, privacy, and the potential for AI to perpetuate existing biases. Overall, the article provides a comprehensive overview of the impact of AI on text assessment and encourages readers to consider both the benefits and challenges of this technology.
[text] Abstract: The use of Large Language Models (LLMs) like ChatGPT has raised concerns in the education community regarding their impact on assessment. The author highlights that AI-generated text is not a new problem, as similar issues exist with the use of search engines and essay-writing services. The truthfulness and trustworthiness of AI-generated text are not exclusive to AI, as people can also write untruthful information. The author suggests that the solution to assessment is not to rely on large texts or quizzes, but to focus on long-term engagement for building reputation. The education system needs to be restructured to keep small class sizes and emphasize 1:1 engagement for quality learning. The author also points out that AIs will play a significant role in our lives and need to be educated to be friendly and not competition.
ADDITIONAL RESOURCES
How to Productively Address AI-Generated Text in Your Classroom
What are ChatGPT and AI-generated text?
How can you most productively address Chat-GPT and other AI text tools?
Why might students use AI-generated text?
How can you identify AI-generated text?
How can you address AI-generated content in your syllabus and course design?
How can you adjust assignments to make them more AI-resistant?
How can you embrace the AI tools for improving student learning?
ChatGPT and AI in Higher Education: Opportunities and Challenges
Presenters: Vivek Astvansh, Paul Cook, Jeanette Heidewald, Rebecca Itow, Kevin Jones
Moderator: Adam Maksl
Recorded Wednesday, January 18, 2023 3 - 4 p.m. EST
A panel of faculty and experts across IU campuses explores the potential uses and challenges of ChatGPT and other AI technologies in teaching and learning. We've seen many media reports in recent weeks about the technology. Discussions have included not only concerns about students using the tool to cheat but also opportunities to use such tech in automating administrative tasks or proactively introducing students to technology likely to shape the future of work.
In this webinar, we provided a brief overview of the technology and explored these topics and more, identifying both challenges and opportunities for teaching and learning. Our panelists provided diverse, cross-disciplinary perspectives. This panel was the first in a series of programs offered across IU campuses on AI and its role in teaching and learning.
Authored by: Makena Neal & Chat GPT
Posted on: #iteachmsu
DID YOU KNOW...
Information on the University’s Anti-Discrimination Policy and how to file a complaint regarding discrimination and/or harassment can be found at:
http://www.oie.msu.edu/
Information on the University’s Anti-Discrimination Policy and how to file a complaint regarding discrimination and/or harassment can be found at:
http://www.oie.msu.edu/
Posted by: Makena Neal
Navigating Context
Posted on: #iteachmsu
According to Derald Wing Sue, “microaggressions are every day encounters of subtle discrimination that people of various marginalized identities experience throughout their lives.” They are often subtle and unintentional and the person who commits a microaggression is often unaware they have hurt someone. Nonetheless, the accumulated impact of daily microaggressions cause real pain, anxiety, depression, self doubt and may even have adverse health impacts on the recipients.
To learn more about microaggressions, click the attachment below.
SOURCE: MSU Office for Inclusion and Intercultural Initiatives
To learn more about microaggressions, click the attachment below.
SOURCE: MSU Office for Inclusion and Intercultural Initiatives
Posted by: Makena Neal
Navigating Context