Program & Abstracts
Wednesday December 11th
10:00a -10:15a PST || 1:00p -1:15p EST
10:15a -11:15a PST || 1:15p - 2:15p EST
Keynote Address: Main Room
Teaching Research Methods Through Replication Studies with The Collaborative Replications and Education Project
Jordan Wagge Avila University The Collaborative Replication and Education Project (CREP) is a framework for organizing student research projects in psychology across institutions, with a focus on replicating recent published work in psychology. The project has a two-part mission: first, to guide student learning through high-quality, rigorous research projects, and second, service to the field by curating data from these high-quality projects to further our understanding of effects and their boundary conditions. In this talk, I will discuss how CREP works, why CREP works, and some early outcome data from studies comparing CREP projects to more traditional projects. I will also discuss how both instructors and students can get involved as contributors, reviewers, and peer mentors, as well as some suggestions for instructors who would like to adapt parts of the CREP framework for their courses or research supervision.
Main Room
Welcome - PsychTerms Organizing Committee
11:20a - 11:40a PST 2:20p - 2:40p EST
Breakout Room A
Digital Intro: Incorporating Data Skills in the Modern General Education Classroom
Lisa Dierker, Abdiasis Daauud Wesleyan University Introductory courses play a vital role in higher education and offer immense potential for dynamic learning experiences. By integrating data projects and technical skills in to general education courses, students can actively engage with disciplinary content through problem-solving, projects, inquiry, and design. To seize this exciting opportunity, we will present emerging work from the Digital Intro initiative, a National Science Foundation funded project aimed at transforming the highest enrollment course in the U.S., Introduction to Psychology, into an empowering, project-based curriculum. The initiative's goal is to enhance students' academic journeys by helping them 1) develop data skills early in their education; 2) pursue further coursework in this area; and 3) plan for careers in the modern data-driven world.
Breakout Room B
Introducing VSSL: A Brief Scale To Evaluate the Perceived Value of Software to Statistical Learning
Alyssa Counsell, Udi Alter, Carmen Dang, Zachary Kunicki Toronto Metropolitan University The biggest difference in statistical training from previous decades is the increased use of software. Assessing the value of software to statistical learning demands appropriate, valid, and reliable measures. In this presentation, we introduce the Value of Software to Statistical Learning (VSSL) scale. Specifically, we report on the psychometric properties of the VSSL scale in an American undergraduate student sample who used SPSS. This brief 7-item measure had strong psychometric support to assess students' perceived value of software in an educational setting. It can be used to assess changes in perceptions over a course or examine perceptions of software value across different types of statistics courses or with different software packages.
15-minute Break
11:55a - 12:15p PST || 2:55p - 3:15p EST
Breakout Room A
Teaching Critical Evaluation of Psychological Findings Using P-Curve Analysis
Alina Hyk, Jannah R. Moussaoui, Jason S. McCarley Oregon State University, Drexel University To be wise consumers of research, undergraduates need skills to evaluate the credibility of psychological findings. We propose the use of p-curve analysis, a meta-analytic technique that assesses evidential value, either through a class project or an in-class activity, as a practical method to help undergraduates critically evaluate psychological findings. Through two student-led projects, we identified three pedagogical benefits of p-curve analysis: 1) uncovering gaps in students' knowledge of study design and statistics. 2) enhancing students' ability to identify critical hypotheses and interpret results, and 3) increasing students' understanding of questionable research practices. In this presentation, we will explain how instructors can use p-curve analysis as an experiential learning activity, and will provide ready-to-use templates for group p-curve projects.
Breakout Room B
A Participatory Approach to Teaching Large-Sized Research Methods in Psychology Courses
Elise Duffau, Rebecca Covarrubias University of California Santa Cruz We redesigned an Introduction to Research Methods in Psychology course at UC Santa Cruz to better emphasize a participatory action research (PAR) approach. A PAR approach centers those who are most impacted by the work, situating students as the main drivers of the research. A teaching team consisting of 12 teaching assistants (TAs), one lead TA, and one faculty instructor launched an active-learning course curriculum focused on student-led PAR projects across 12 sections. Section teams co-constructed a single research question centered on students' experiences and student success at UC Santa Cruz. Team projects culminated into scholarly papers and more accessible products (e.g., abstracts, infographics, research briefs) to communicate their findings to and to engage with the broader campus community.
12:20p - 12:40p PST || 3:20p - 3:40p EST
Breakout Room A
Are We Actually Introducing Students to Statistics? Teaching Introductory Statistics as a Course in Statistical Literacy and Critical Thinking
Matthew S. Fritz University of Nebraska-Lincoln Why can students calculate t statistics but seem unable to evaluate the trustworthiness of statistics on social media? By focusing on using software to create statistics, introductory statistics courses are failing to actually introduce students to the field of statistics. The current paper discusses redesigning an introductory statistics course to focus on statistical literacy and critical thinking through a series of additional readings that provide context to the statistical content. In class discussions help students apply these concepts to evaluate statistics they encounter in research and their everyday lives. These concepts are further incorporated into statistical assignments where students must reflect on the limitations of the results in their interpretation. Initial results suggest a deeper understanding of the statistical content when provided with this additional context.
Breakout Room B
Advancing Racial Equity in Undergraduate Statistics through Systems Improvement
Ji Son, Matthew Jackson, Claudia Sutter, Mariela Rivas California State University, Los Angeles This talk introduces the Better Book approach (Stigler et al., 2020), a collaborative research and development model where researchers, instructors, and developers use data to improve student experiences with course materials. We show how this approach can help close equity gaps in introductory statistics courses, especially for Latine students in California's public universities. Longitudinal data collected across 12 chapters of an interactive textbook revealed motivational inequities between racially marginalized and non-marginalized students. In response, the Better Book community redesigned the textbook, resulting in improved experiences for all students and narrowing motivational gaps. Attendees will learn how a systems improvement approach can enhance our individual efforts to create more inclusive learning environments and advance equity.
Poster Session (gather.town)
12:45p - 2:00p PST || 3:45p - 5:00p EST
Uncovering Plot Twists in Data: Fostering Curiosity and Engagement in Statistics
Mariela Rivas, Ji Son University of California, Los Angeles, California State University, Los Angeles Engaging students in statistics isn’t just about finding “relevant” datasets; it’s about revealing compelling stories within the data itself. Rather than relying on students’ initial interest, our approach uses "plot twists" to spark curiosity and motivate deeper learning of statistics concepts. Jupyter notebooks allow us to present data and guide students on a narrative journey to discover surprising patterns. For example, a notebook analyzing tadpole egg-eating behavior invites students to visualize and model data. But students end up uncovering a surprising cannibalistic pattern that highlights the importance of including interaction terms—considering the presence of the tadpole and egg species. By guiding students to find plot twists in data, we shift the focus from superficial relevance to genuine statistical curiosity.
The Deception Lab: Building a Research Informed Teaching Lab To Enhance Student Learning
Cody N. Porter University of the West of England (UWE) Bristol Learning about research methods is often challenging for students who are new to the university environment. This talk addresses the challenge of making research methods relevant and engaging for students through a ‘Deception Lab’ for Psychology and Criminology students. By integrating a research-informed teaching lab at the University of the West of England (UWE) Bristol, students actively participate in co-creating projects, enhancing their practical skills and understanding of research methodologies. The course combines lectures, workshops, and lab sessions, emphasizing experiential learning. Implementation involved team-based projects with real-world applications, guided by continuous feedback. The approach has proven effective, with increased student engagement and improved research skills, aligning with evidence-based pedagogy.
Trust and Motivation Towards Scientific Research: Impacts of Direct Participation in Replication Research Studies
Jade Roghair, Amanda Mae Woodward University of Minnesota As a result of the replication crisis, psychology instructors have posed the idea of including replication studies in undergraduate statistics courses (Frank et al, 2012). In the current study, we examined how participating in a replication study related to students’ perceptions of replication studies. Undergraduate students in a psychology statistics course completed a survey concerning their beliefs in research. Students then completed the dependent measures from DeNeys et al (2013). Upon running analyses on the data collected, students ranked their level of engagement. Overall, students found these exercises helpful for their learning (p
Are We Overstating the Ubiquity of Statistics Anxiety in Psychology? Meta-Analytic Evidence and Insights
Johanna Loock, Laura Bandi, Alyssa Counsell Toronto Metropolitan University Psychology statistics educators commonly describe statistics anxiety as a significant issue in their classrooms. Although previous research findings suggest that statistics anxiety has negative consequences such as decreased performance, the prevalence of statistics anxiety has not been established. In this presentation, we will describe a meta-analysis investigating the degree to which students experience statistics anxiety, as measured by mean responses to subscales on the Statistics Anxiety Rating Scale. Data reflect responses from over 15 000 participants within 111 global samples. We find no evidence of substantial statistics anxiety, indicating that this issue may not be as prevalent as previously assumed, or that the Statistics Anxiety Rating Scale does not capture statistics anxiety as experienced in the statistics classroom.
From Curiosity to Competence: Teaching Students To Ask the Right Questions With the Four Validities
Shaina Rowell Wilkes Honors College of Florida Atlantic University The first step on a student’s journey of learning how to evaluate psychological research is being able to ask the right questions. A common framework in psychology is to evaluate four validities: construct, statistical, and external for any claim as well as internal for causal claims. Students enter a research methods class with intuitive questions, but these tend to be narrow. My goals are that students leave my class with a greater diversity of questions to ask, a better understanding of which questions go in a category together, and an appreciation for how researchers often must prioritize certain validities over others when making design decisions. In this poster, I present assignments that integrate the four validities and data on the types of questions my students ask about validities across the semester.
Statistics that Stick: A Statistics in the Behavioral Sciences Portfolio Assignment to Promote Lasting Knowledge
Jordyn Wilcox University of Notre Dame What statistical test is used to compare group means for a within-subjects experiment with one independent variable and only two levels? Student response when actively in my Statistics for Behavioral Sciences course: “A paired t-test!”. That same student six months later in my Methods course: “[a blank stare] no idea…”. As an educator, one of my primary goals is to instill lasting knowledge that students can implement after they leave my classroom. Thus, I am piloting a new “Statistics Portfolio” assignment in which students curate a multi-chapter resource intended to serve them both during and after my course. Core components include applicable study designs, essential formulas, and step-by-step narratives using meaningful and relevant prompts in SPSS to promote knowledge that “sticks”.
Practice Makes Perfect: Statistics Lab Policies
Alannah Shelby Rivers Texas Woman's University I will discuss my course policies regarding statistics lab resubmissions in an Applied Statistics course. Each student works with a single individualized data set for all 10 labs over the course of the semester. All labs include both output and interpretation, with a simple 5-point rubric to minimize grading time and maximize feedback. “Soft” deadlines are weekly, with unlimited resubmissions until the “hard” deadlines immediately before each exam. I will explain some of the benefits of this approach for equity, as well as some challenges I have faced.
Developing a Research Proposal: A Scaffolded Approach in a Clinical Mental Health Counseling Program
Tracy N. Baker Lynn University It is common for students interested in pursuing helping professions to have little to no desire to conduct research professionally. The goal of this redesigned research assignment was two-fold: 1) address AI concerns experienced in higher education and, 2) mentor students in the development of a hypothetical research study of their interest. Students are encouraged to choose hypothetical participants and variables of interest within the first two weeks of the course. Scaffolded throughout the semester, students submit weekly assignments on their progress, including annotated bibliographies of relevant literature, descriptions of the selected variables and populations, and their proposed methodology: which culminates in a final research poster. Weekly feedback and group discussion facilitates the development of this proposed hypothetical research study.
Parsimony in Peril: The "International Movie Villain Hypothesis"
Jeff Bowen Johns Hopkins University A testable and falsifiable hypothesis is presented (after introducing those principles): "All movie villains are portrayed by international actors." Students generate examples that support this hypothesis, and then identify a counter-example. The hypothesis is amended to "All SUPERHERO movie villains...". The same procedure unfolds. It is amended further to "All FLYING SUPERHERO movie villains...". The procedure unfolds again. The futility of the increasingly idiosyncratic adjustments are used to debrief about the value of parsimony in hypothesis generation. The content area (i.e., movie villains) can be modified to one's audience ("All SOCIAL MEDIA PLATFORMS have blue logos..."). or class This activity can also be adapted to highlight distinctions between moderating variables and ill-specified hypotheses in discussions of individual differences and context effects as well.
Harnessing Collaboration: Mock Exams as an Innovative Tool to Reduce Anxiety and Enhance Self-Efficacy in Statistics Courses
Kristof Csaba, Miranda McIntyre California State University San Bernardino This study addresses high statistics anxiety among undergraduates, which negatively impacts performance and self-efficacy. To reduce anxiety and improve self-efficacy, collaborative mock exams were introduced in an introductory statistics course. Students completed practice exams individually or in pairs, with mock exams reflecting actual course content. Results showed that students in the collaborative condition experienced significantly lower anxiety than those in the individual condition, while both groups saw an increase in self-efficacy. These findings align with evidence-based pedagogy, demonstrating that collaborative learning reduces anxiety and enhances understanding. This innovative approach integrates peer collaboration with practice testing to support learning and address emotional barriers, aligning with themes of innovative teaching activities and scholarship of teaching.
ReCentering Correlation: An Open-Source Textbook Using R for Psychologists
Jessica Fossum Seattle Pacific University The open-access chapter on correlations in ReCentering Psychological Statistics offers an innovative approach to teaching advanced undergraduate statistics. By challenging traditional centering practices—often rooted in a WEIRD framework—this chapter can be used as a tool to foster a more inclusive learning environment. Utilizing the open-source program R, it provides practical examples and vignettes from diverse researchers, emphasizing justice, equity, and inclusion. This particular chapter goes in-depth with correlations, including how to report correlation tables in APA format. With practice problems included and a walk-through screencast of performing these analyses, this chapter serves as a valuable asset for professors seeking to enhance their curriculum and support diverse perspectives in statistical education.
Using Mastery Learning Assignments in Teaching Undergraduate Statistics
Daniel Clark Texas A&M University - Central Texas To infuse low-stakes retrieval practice into statistical analyses, a new tool was created, called the mastery-based quest (or “quest,” as I call them in class) for helping students get more practice and support while learning to analyze data. These assignments are pre-programmed web-based forms that ask the questions, requiring the students to analyze data and achieve correct answers at least once (with proper in-person or virtual support) before they complete the assignment. Then once the assignment is complete, the students receive a participation grade for completing them.
Thursday December 12th
10:00a -10:15a PST || 1:00p -1:15p EST
10:15a -11:15a PST || 1:15p - 2:15p EST
Keynote Address: Main Room
Data with a Conscience: Integrating Ethics into Psychology Curricula
Susan A. Nolan Seton Hall University In this presentation, I’ll explore the critical importance of integrating data ethics into psychology curricula, with a focus on statistics and research methods courses. I’ll discuss some of the ethical challenges arising from data collection, analysis, and interpretation in psychological research. And I’ll share some concrete examples and practical strategies for instructors to incorporate ethical considerations across the psychology curriculum. Topics will include positionality considerations, sampling issues, privacy (and other) concerns in data collection, addressing bias in research design and analysis, and ethical and transparent reporting of results. By the end of this session, attendees will have a toolkit of engaging activities and examples to effectively teach data ethics, preparing students for the growing complexities of modern psychological research and practice.
Main Room
Welcome - PsychTerms Organizing Committee
11:20a - 11:40a PST || 2:20p - 2:40p EST
Breakout Room A
The Dance of the Means – A Free, Interactive, Online Simulation for Fostering Statistical Thinking
Robert Calin-Jageman, Geoff Cumming Dominican University, La Trobe University Simulations can provide a rich playground for students to develop statistical thinking. We'll present our latest version of the Dance of the Means, a free, online simulation for guided exploration of sampling theory (https://esci.thenewstatistics.com/). WIth the Dance of the Means, students can explore the vagaries of sampling, the central limit theorem, the influence of sample size and population variation on sampling error, the fit between expected sampling error and actual sampling error, and the long-run capture rate of confidence intervals. Students can draw samples fromnormal distributions, skewed distributions, and can even draw their own distributions. A companion Dance of the r Values provides a chance to conduct similar explorations for correlational studies. We'll provide an overview of these exciting tools and provide materials you can adapt to your own teaching context.
Breakout Room B
Encouraging Student Belonging in Statistics Classrooms
Amanda Mae Woodward University of Minnesota Introductory statistics courses can be challenging for psychology students. Despite these relatively common struggles with statistics, students can feel like they are the only one in the room struggling. This perception can lead to feelings of isolation and decreased belonging, which can prevent students from engaging with the material and learning it effectively. In this talk, I will discuss ways to promote feelings of belonging in large introductory classrooms. Specifically, I will discuss ways to build rapport between instructors and students, between students and their peers, and to help students find connection in the classroom more generally. After discussing these strategies, I will share student data on belongingness and how their qualitative and quantitative data relate to students’ own learning.
15-minute Break
11:55a - 12:15p PST 2:55p - 3:15p EST
Breakout Room A
Population Professorville
Karen H. Larwin, David A. Larwin Youngstown State University, Kent State University Salem In this online graduate statistics course, students engage in hands-on learning by analyzing unique random samples drawn from a large dataset provided by the instructor. Each student receives a sample of 200 cases, allowing them to collaborate on assignments while obtaining individual results. This structure encourages students to compare their findings with the population data (the instructor's results) to better understand sampling error and variability. The course covers a range of statistical techniques, from descriptive statistics to multiple regression, reinforcing key concepts such as sampling, statistical inference, and data analysis. By working with real-world data, students gain practical experience and a deeper understanding of statistical principles in a collaborative yet independent learning environment.
Breakout Room B
Building Better Writers: Scaffolding Research for Student Success
Gabriela Martorell Virginia Wesleyan University Despite its importance, many students feel underprepared for academic writing (Aron & Roska, 2011. Fortunately, writing can be improved with practice (Barzelai et al., 2018). This demonstration presents a scaffolded research synthesis assignment. Students first work in small groups to analyze abstracts from 5 studies (3 with converging results, 1 irrelevant, 1 contradictory), condensing each into 1 sentence and then synthesizing the 4 most relevant into a cohesive paragraph. Groups share their paragraphs, and the top group wins a prize. Next, students complete a similar task at home. Finally, they select 3 variables for their final research proposal and locate 3 relevant studies for each. Using the synthesis process, they produce 3 paragraphs of evidence to support their proposal. This assignment builds research synthesis skills and scaffolds their final project.
12:20p - 12:40p PST 3:20p - 3:40p EST
Breakout Room A
Enhancing Statistical Literacy: Estimation Statistics as an Alternative to Understanding Research
Mircea Zloteanu Kingston University London Estimation statistics improve the teaching of statistics by emphasizing effect sizes, confidence intervals, and visualization over traditional hypothesis testing. By focusing on understanding the magnitude and uncertainty of effects rather than dichotomous judgments based on confusing metrics (p-values), students gain a deeper, more nuanced understanding of data and its implications. When employed with students learning statistics and experimental design for the first time the approach shows substantial improvements in understanding, competence in use, and grades. Estimation statistics foster students' abilities to interpret and communicate statistical results effectively. Practical strategies to integrate estimation techniques in classrooms will be discussed, with focus on open materials and software to easily implement the approach, creating a more statistically literate student body.
Breakout Room B
Leveraging Hands-On Activities To Help Novice Learners in Statistics and Data Science
Icy(Yunyi) Zhang University of Wisconsin-Madison Novice learners in statistics and data science courses often struggle to develop meaningful comprehension of the abstract concepts in the domain. Embodied pedagogies, which use bodily movement to facilitate cognitive change through enactment, observation, or mental simulation of actions (Clark, 2008; Tytler & Prain, 2013; Wilson, 2002), offer a promising solution. As I delved into the nuances of how embodied pedagogies influence learning, I recognized the importance of moving beyond the question of whether a particular approach is effective for all learners. Through innovative design of an eight-week classroom intervention, I found that learners with low prior knowledge benefited more from actively performing actions and gestures, while high-prior knowledge learners gained more from observing others.
Poster Session (gather.town)
12:45p - 2:00p PST 3:45p - 5:00p EST
Diversifying the Psychological Science Pipeline with SOAR, an Undergraduate Research Program for Minority High School Students
Lisa Worthy Glendale Community College Previous studies have demonstrated that participation in student research builds critical thinking skills and analytical ability (Lopatto, 2003; Seymour, Hunter, Laursen, & DeAntoni, 2003), and that undergraduate students who participate in research are more likely to finish a baccalaureate degree and go on to graduate school (Kinzie, 2010; Lopatto, 2007; Nagda et al., 2003). We decided to implement this high impact practice with high school students from underrepresented groups in the hopes of encouraging them to attend college, and specifically, to consider science in general, and psychology in particular, as a major.
Hands-on Projects in GenEd Statistics Help Students Demonstrate Quantitative Literacy
Anne E. Stuart, Jenna M. Gray, Heidi R. M. O'Connor American International College We redesigned our GenEd statistics course to enhance student engagement and relevance through project-based learning. Students work in small groups (typically 3-4 students) to complete a semester-long project that includes developing a research question, conducting a basic search of the literature, generating testable hypotheses, designing a simple survey to test the hypotheses, collecting survey responses, analyzing the collected data, communicating the findings in a poster, and presenting the poster at a campus-wide poster session. We evaluated student posters using the AAC&U Quantitative Literacy Rubric, revealing an average score of 1.88 (SD = .34). The dimension of Calculation scored the highest, while Assumptions scored the lowest.
Introduction to Statistics: Choose Your Own Software Adventure
Baine B. Craft Seattle Pacific University Psychology majors and minors benefit from access to graduate programs and careers in a wide range of disciplines, both within and outside of psychology (e.g., business and health professions). As a result, students have varying needs when it comes to statistical software. Likewise, students differ in which specific software best aligns with their graduate school and career goals. Given this diversity needs within introduction to statistics classrooms, I have developed a method for teaching introductory statistics that allows students to choose the software (e.g., Excel, JASP, SPSS) that best suits their career and graduate school needs. This approach utilizes asynchronous screencasts and discipline-specific examples while maintaining a sense of community and social presence within the classroom. Furthermore, it can be delivered in online, blended or hybrid, or in-person formats.
Hand Calculations vs. Software? Student Attitudes About Their Value Mirror Their Instructors
Laura Bandi, Johanna Loock, Alyssa Counsell Toronto Metropolitan University This study investigated differences in attitudes towards statistics and statistics anxiety across two sections of an introductory statistics course - one that focused on hand calculations and another that focused on software (jamovi). We found minimal differences on statistics attitudes and anxiety across the two approaches. Instead, instructor rapport was the factor most strongly associated with reduced anxiety and more positive attitudes. Additionally, at the end of the course, students overwhelmingly preferred the method emphasized by their instructor: those in the hand calculations course rated hand calculations significantly higher than those in the software course. Conversely, students in the software course preferred software over hand calculations. This research emphasizes the impact of instructors on shaping students’ attitudes and perceptions in the statistics classroom.
Implementation of a Flexible Due Date Policy To Equitably Support Students in a Psychology Research Methods Course
Stefanie S. Boswell University of the Incarnate Word I implemented a flexible due date policy called a psychology research methods course. It extended two due dates up to one additional week for students who did not qualify for another university-related extension. I invited students to complete an anonymous survey about the perceived benefits of the policy. Eleven students responded and reported significantly positive perceptions of the policy’s benefits for management of stress and workload as well as improved engagement and learning. The poster addresses students’ perceived impacts of the policy and also provides recommendations for its implementation. The policy was an easy-to-implement way to support equitable access to course learning and success.
Effects of Teaching Open Science to Undergraduates
Yueping (Quartney) Qian*, Colm Smith*, Carmen Farrell, Amanda Mae Woodward University of Minnesota Twin Cities Psychological research is increasingly emphasizing transparency and integrity, promoting open science practices such as preregistration, open data, and related platforms (Foster, Deardorf, OSF. 2017). Preregistration, a public document in which researchers outline their research design, hypotheses, and analysis plan prior to data collection, is an important aspect of open science because it can reduce questionable research practices and increase trustworthiness. This study explores how learning about preregistration affects students’ perceptions of research and of the preregistration process. Data were collected in an introductory statistics course at a large midwestern university. Our results indicate significant positive shifts in students' views toward preregistration after completing a preregistration (p’s
Flipped Classrooms in Action: Fostering Collaboration and Active Learning
Serena Zadoorian University of California Riverside, California State University San Bernardino To enhance engagement and support students with various learning styles in a lower-division research methods course, materials from PsycLearn were used. This educational support enabled me to utilize the flipped classroom method, allowing for more discussion time in class. Students were instructed to review the lecture materials before class and post at least one question they found confusing on the Canvas discussion board, which allowed for more discussion time in the classroom. Finally, to foster collaborative participation, students were randomly assigned to groups of 4-5 to engage in weekly in-class activities related to that week’s materials. Toward the end of the semester, students highlighted their satisfaction and appreciation for the course structure and support provided.
Student Perceptions of AI in an Introductory Statistics Classroom
Alexandra Ingrassia, Melissa O'Neil University of Minnesota It’s important to understand the effects of AI in academics. The study explores how students perceive chatGPT, the benefits of conversational AI, and potential drawbacks. Students were randomly assigned to complete a set of statistics assignments 1) without using Chat GPT, 2) using Chat GPT however they wanted, and 3) using a scaffolded set of prompts with Chat GPT. Prior to the assignments, students indicated how often they used ChatGPT, their views on conversational AI, and drawbacks perceived. After the assignments, students completed the same questionnaires and described their experience using AI. Students had feedback ranging from positive to negative. These findings are important because they can aid in development of teaching curriculums as statistics courses adapt to technological advancements.
Student Well-Being, Engagement, Homework Habits, and Sensitivity to Constructive Alignment: Insights From Start- and End-of-Class Surveys in Psychological Statistics
Jeff Bowen Johns Hopkins University Over the last year, I have administered weekly start- and end-of-class surveys to undergraduates in my psychological statistics course. The start-of-class surveys assess their wakefulness, course-external stressors, and assignment completion habits (e.g., use of lecture materials, textbook, AI, peer support, etc.). The end-of-class surveys assess their self-reported engagement with the day's material, level of understanding, and perceived utility of their learning for upcoming assessments. The goal of this investigation was to determine which factors assessed at the start of class predict positive experiences during the class (e.g., do students who are especially tired on a given day still manage to appreciate that material from class is directly tied to their next assignment's tasks?), and if those factors, in turn, predict performance on the next assignment/assessment.
Representation Matters: Hyper-Minoritized Students Are More Likely To Relate and Engage With Content From a Demographically Similar Instructor
Maisha Ahasan, V. N. Vimal Rao Toronto Metropolitan University, University of Illinois Urbana-Champaign Sense of belonging (S.O.B) is essential for student engagement and motivation. A student’s racial identity is related to their S.O.B. – non-white students are less likely to feel a strong S.O.B., especially when their identity is incongruent with their instructor. This effect is stronger for “hyper-minority” students, those in relatively small ingroups (e.g., South Asians in North America). We recruited 573 students in a statistics course taught by a South Asian-American professor. Students who shared a racial identity with the instructor were 1.55 times as likely to find the instructor relatable. Those who found the instructor relatable were 3.36 times as likely to take another statistics class, but only with the same instructor. We show that demographic similarity is critical in enhancing S.O.B. and educational motivation for hyper-minorities.
Quantitative Researchers Are People Too: Discussing Researcher Positionality and Reflexivity in an Introductory Statistics Course
Matthew S. Fritz, Rachel Fouladi University of Nebraska-Lincoln, Simon Fraser University Positionality and reflexivity are not often discussed in statistics courses. But that does not mean that quantitative researchers are unaware of these concepts or consider them unimportant. Instead, quantitative researchers often aim to limit the impact of researcher bias through their design choices. Presenting statistics as one Way of Knowing and discussing how quantitative researchers address positionality in their research early in an introductory statistics course can help students, some of whom view statistics as inherently biased, understand the relationship between quantitative and qualitative methods. Requiring students to reflect on their positionality and how it could affect their own quantitative research allows for experiential learning. Initial results suggest more openness to learning quantitative methods and a deeper understanding of the material.
Using ChatGPT to Create Scenarios for In-Class Discussions on Ethical Guidelines
Rachel Walker University of the Incarnate Word This presentation explores the innovative application of ChatGPT in creating scenarios for student discussions, offering an AI-powered approach to enhance educational experiences. It begins with an introduction to ChatGPT, creating research scenarios, and outlines the benefits of using this technology in academic settings. The core focus is on how ChatGPT can streamline and enhance the creation of realistic scenarios that increase student engagement, participation, and enthusiasm.