Core Publications
The Better Book Approach for Education Research and Development
This paper describes a new approach for education research and development - the better book approach - and reports on our initial development and application of the approach in the context of introductory college-level statistics.
Download NowPracticing Connections: A Framework to Guide Instructional Design for Developing Understanding in Complex Domains
Research suggests that expert understanding is characterized by coherent mental representations featuring a high level of connectedness. This paper advances the idea that educators can facilitate this level of understanding in students through the practicing connections framework: a practical framework to guide instructional design for developing deep understanding and transferable knowledge in complex academic domains.
Download NowModeling First: Applying Learning Science to the Teaching of Introductory Statistics
In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help students build a coherent and interconnected representation of the domain. The resulting practicing connections approach provides students with repeated opportunities to practice connections between core concepts (especially the concepts of statistical model, distribution, and randomness), key representations (R programming language and computational techniques such as simulation and bootstrapping), and real-world situations statisticians face as they explore variation, model variation, and evaluate and compare statistical models. We provide a guided tour through our curriculum implemented in an interactive online textbook (CourseKata.org) and then provide some evidence that students who complete the course are able to transfer what they have learned to the learning of new statistical techniques.
Download NowTeaching Statistics and Data Analysis with R
In this exploratory study, we characterize the attitudes and experiences of 672 undergraduate students as they used our online textbook as part of a 10-week introductory course in statistics. Students expressed negative attitudes and concerns related to R at the beginning of the course, but most developed more positive attitudes after engaging with course materials, regardless of demographic characteristics or prior programming experience. Analysis of a subgroup of students revealed that change in attitudes toward Rmay be linked to students’ patterns of engagement over time and students’ perceptions of the learning environment.
Download NowAll Publications
Prediction versus production for teaching computer programming
Background: Most students struggle when learning to program. Aims: In this paper we examine two instructional tasks that can be used to introduce programming: tell-and- practice (the typical pedagogical routine of describing some code or function then having students write code to practice what they have learned) and prediction (where students are given code and asked to make predictions about the output before they are told how the code works). Sample: Participants were 121 college students with no coding experience. Methods: Participants were randomly assigned to one of two parallel training tasks: predict, or tell-and-practice. Results: Participants in the predict condition showed greater learning and better non-cognitive outcomes than those in the tell-and-practice condition. Conclusions: These findings raise a number of questions about the relationship between programming tasks and students’ experiences and outcomes in the early stages of learning programming. They also suggest some pedagogical changes to consider, especially in early introductions to programming.
Download NowLatine Students’ Motivational and Emotional Experiences Related to Their Introductory Statistics Course: Differences by Institution Type Necessitate Tailored Interventions
The present study developed a representation-mapping intervention designed to help students interpret, coordinate, and eventually translate across multiple representations. We integrated the intervention into an online textbook being used in a college course, allowing us to study its impact in a real course over an extended period of time. The findings of this study support the efficacy of the representation-mapping intervention for facilitating learning and shed light on how to implement and refine such interventions in authentic learning contexts.
Download NowLower Socioeconomic Status is Related to Poorer Emotional Well-Being Prior to Academic Exams
People of lower social status tend to have greater emotional responses to stress. This study assessed whether lower social status was related to greater emotional responses in anticipation of a naturalistic stressor: academic exams among college students. As hypothesized, multilevel models (ratings nested within participants) predicting emotion indicated that students with lower mother’s education had less positive emotion, more depressive emotion, and more anxious emotion the day prior to academic exams than students with higher mother’s education (proportional reductions in variance [PRV] = .013–.020). Specifically, lower mother’s education was associated with poorer well-being before but not after the exam. Exploratory models revealed that differences in emotion by mother’s education were strongest for students with lower exam scores (PRV = .030–.040).
Download NowConcerns and Challenges in Introductory Statistics and Correlates with Motivation and Interest
We explore how students’ course concerns at the outset of their introductory statistics course predict their later perceived course challenges and future interest in statistics via a function of achievement motivation. Data were collected from undergraduate students during the COVID-19 pandemic, using both open-ended (concerns and challenges) and closed-ended (achievement motivation and future interest) questions. Our findings (a) add to the increasing body of research reporting differences in how female and male students as well as students from racially marginalized backgrounds and racial majority students experience STEM courses and help explain different levels of interest in pursuing STEM careers, and (b) suggest that increasing future interest in statistics might require different interventions.
Download NowWatching a Hands-On Activity Improves Students’ Understanding of Randomness
Given the growing interest in using statistical programming languages like R as pedagogical tools, the findings of this study provide important and encouraging insights into the use of hands-on demonstrations to complement computer simulation in remote teaching. It validates the importance of giving students some hands-on exposure to the simulation processes prior to the computational simulation we want them to understand and makes it clear that at least some of the benefits of embodied activities can be retained even if students are not performing the hands-on activities themselves.
Download NowStudent Concerns and Perceived Challenges in Introductory Statistics
This study explored undergraduates’ incoming course concerns and later perceived challenges in an introductory statistics course using the CourseKata materials. Concerns changed with the onset of COVID-19 and the frequency of concerns differed by gender and URM status. Because students’ perceptions have an impact on their experiences and expectations, understanding and addressing concerns and challenges can help guide the development of interventions.
Download NowReasoning Affordances with Tables and Bar Charts
We tested whether confirmation bias exists when people reason with visualized data and whether certain visualization designs can elicit less biased reasoning strategies. We asked crowdworkers to solve reasoning problems that had the potential to evoke both poor reasoning strategies and confirmation bias. Presenting the data in a table format helped participants reason with the correct ratio strategy while showing the data as a bar table or a bar chart led participants towards incorrect heuristics. Confirmation bias was not significantly present when beliefs were primed, but it was present when beliefs were pre-existing. Additionally, the table presentation format was more likely to afford the ratio reasoning strategy, and the use of ratio strategy was more likely to lead to the correct answer.
Download NowTeaching Statistics and Data Analysis with R
In this exploratory study, we characterize the attitudes and experiences of 672 undergraduate students as they used our online textbook as part of a 10-week introductory course in statistics. Students expressed negative attitudes and concerns related to R at the beginning of the course, but most developed more positive attitudes after engaging with course materials, regardless of demographic characteristics or prior programming experience. Analysis of a subgroup of students revealed that change in attitudes toward Rmay be linked to students’ patterns of engagement over time and students’ perceptions of the learning environment.
Download NowInstructed Hand Movements Affect Students’ Learning of an Abstract Concept from Video
The two studies reported here investigate the impact of instructed hand movements on students’ subsequent understanding of a concept. Students were asked to watch an instructional video—focused on the concept of statistical model—three times. These two studies found that instructed hand movement—even when presented as an unrelated, secondary task—can affect students’ learning of a complex concept.
Download NowThis article was featured in Scientific American.
Download NowUtility Value Trajectories and their Relationship with Behavioral Engagement and Performance in Introductory Statistics
This study examined utility value trajectories overall and by gender, race, and underrepresented racial minority (URM) status within an introductory statistics course that used the CourseKata online textbook and tested the relationships between utility value, behavioral engagement, and performance.
Download NowPracticing Connections: A Framework to Guide Instructional Design for Developing Understanding in Complex Domains
Research suggests that expert understanding is characterized by coherent mental representations featuring a high level of connectedness. This paper advances the idea that educators can facilitate this level of understanding in students through the practicing connections framework: a practical framework to guide instructional design for developing deep understanding and transferable knowledge in complex academic domains.
Download NowModeling First: Applying Learning Science to the Teaching of Introductory Statistics
In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help students build a coherent and interconnected representation of the domain. The resulting practicing connections approach provides students with repeated opportunities to practice connections between core concepts (especially the concepts of statistical model, distribution, and randomness), key representations (R programming language and computational techniques such as simulation and bootstrapping), and real-world situations statisticians face as they explore variation, model variation, and evaluate and compare statistical models. We provide a guided tour through our curriculum implemented in an interactive online textbook (CourseKata.org) and then provide some evidence that students who complete the course are able to transfer what they have learned to the learning of new statistical techniques.
Download NowThe Better Book Approach for Education Research and Development
This paper describes a new approach for education research and development - the better book approach - and reports on our initial development and application of the approach in the context of introductory college-level statistics.
Download NowRemoving Opportunities to Calculate Improves Students' Performance on Subsequent Word Problems
This paper reports our investigation on whether removing opportunities to calculate could improve students’ subsequent ability to solve similar word problems
Download NowExploring the Practicing-connections Hypothesis: Using Gesture to Support Coordination of Ideas in Understanding a Complex Statistical Concept
This paper presented a framework and approach for studying how students come to understand complex concepts in rich domains. Specifically, it explores the role that a teacher’s gesture might play in supporting students’ coordination of two concepts central to understanding in the domain of statistics: mean and standard deviation.
Download NowExpertise and Expert Performance in Teaching
This chapter tries to take a broader approach to understanding the nature and development of expertise and expert performance in teaching. The paper also tries to integrate a number of ideas and findings from literatures as diverse as cross-cultural compar- isons of teaching, cognitive psychology, and systems improvement, among others.
Download NowDoes VAM + MET = Improved Teaching?
The paper discusses the logic of the more traditional approach on which many current policies for improving teaching in the United States are based and then presents an alternative research approach, in which a different theory of improvement is assumed.
Download NowOnline Learning as a Wind Tunnel for Improving Teaching
The chapter proposes an approach that combines the affordances of online learning with the methodologies of systems improvement. It discusses how online learning might be a wind tunnel for the study and improvement of teaching.
Download NowWhat Community College Developmental Mathematics Students Understand about Mathematics, Part2: The Interviews
Following the prior paper, this article presents findings from one-on-one interviews with a sample of community college developmental math students. These interviews were designed to further probe students’ mathematical thinking, both correct and incorrect.
Download NowWhat Community College Developmental Mathematics Students Understand about Mathematics
This paper investigates what community college students actually understand about the mathematics that underlie the topics they’ve been taught and seeks evidence that students used reasoning in answering mathematical questions.
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