Leveraging Non-cognitive Student Self-reports to Predict Learning Outcomes

Metacognitive competencies related to cognitive tasks have been shown to be a powerful predictor of learning. However, considerably less is known about the relationship between student’s metacognition related to non-cognitive dimensions, such as their affect or lifestyles, and academic performance. This paper presents a preliminary analysis of data gathered by Performance Learning Education (PL), with respect to students’ self-reports on non-cognitive dimensions as possible predictors of their academic outcomes. The results point to the predictive potential of such self-reports, to the importance of students exercising their self-understanding during learning, and to the potentially critical role of incorporating such student’s self-reports in learner modelling

Human Computation and Convergence

Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing information will tend toward capabilities that derive from our most complex cognitive processes, e.g., abstraction, creativity, and applied world knowledge. Through the advancement of human computation - methods that leverage the respective strengths of humans and machines in distributed information-processing systems - formerly discrete processes will combine synergistically into increasingly integrated and complex information processing systems. These new, collective systems will exhibit an unprecedented degree of predictive accuracy in modeling physical and techno-social processes, and may ultimately coalesce into a single unified predictive organism, with the capacity to address societies most wicked problems and achieve planetary homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added references to page 1 and 3, and corrected typ

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

Leveraging Douyin for Enhanced Learning Motivation: A Study on Educational Strategies and Student Attitudes

This study investigates the integration of Douyin, known globally as TikTok, in educational settings to enhance student learning motivation. The research aims to understand how the use of Douyin, a platform predominantly used for entertainment, can be effectively repurposed for educational purposes. The study is structured around several key areas: student engagement, self-regulation, teacher facilitation, peer collaboration, personalized learning, and student attitudes towards using Douyin in an educational context. A mixed-method approach is employed, involving both quantitative and qualitative data collection through surveys, interviews, and observational studies. The quantitative data assesses the impact of Douyin on various learning motivation factors, while qualitative data provides in-depth insights into student and teacher experiences. The findings suggest that when used strategically, Douyin can significantly enhance student engagement, promote active learning, and foster a positive learning environment. The study also highlights the importance of teachers’ roles in facilitating effective use of Douyin and the influence of student attitudes on learning outcomes.This research contributes to the growing body of knowledge on digital technology in education, offering practical implications for educators seeking to integrate social media platforms like Douyin into their teaching practices

Is Seeing Believing? Leveraging Modality and Similarity in a Belonging Intervention

Students who feel a greater sense of belonging in college often experience more positive academic outcomes. Social-psychological interventions have been shown to improve students’ sense of belonging. However, few studies have examined the social cognitive mechanisms through which interventions work. The purpose of this study was to investigate the influence of two such mechanisms—delivery modality and students’ perceived similarity to peer models—on the efficacy of a narrative-based, social belonging intervention. First-year students (N = 1,329) from a public, land-grant university in the southeastern U.S. were randomly assigned to a social belonging intervention (i.e., a video- or written-based narrative from peers normalizing the adjustment to college) or a control group. The written belonging intervention reduced achievement gaps between first-generation and continuing-generation students. Both intervention conditions reduced achievement gaps between first-generation, racial minority students and their continuing-generation, White peers. Delivery modality predicted students’ perceived similarity, such that students in the written belonging condition felt more similar to peers in intervention materials. Perceived similarity to peer narrators in intervention material did not mediate the relationship between the intervention and student outcomes. Understanding intervention mechanisms could help educational researchers develop more effective interventions to support students’ transition to and performance in college

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

The Long-Run Impacts of Same-Race Teachers

Black primary-school students matched to a same-race teacher perform better on standardized tests and face more favorable teacher perceptions, yet little is known about the long-run, sustained impacts of student-teacher demographic match. We show that assigning a black male to a black teacher in the third, fourth, or fifth grades significantly reduces the probability that he drops out of high school, particularly among the most economically disadvantaged black males. Exposure to at least one black teacher in grades 3-5 also increases the likelihood that persistently low-income students of both sexes aspire to attend a four-year college. These findings are robust across administrative data from two states and multiple identification strategies, including an instrumental variables strategy that exploits within-school, intertemporal variation in the proportion of black teachers, family fixed-effects models that compare siblings who attended the same school, and the random assignment of students and teachers to classrooms created by the Project STAR class-size reduction experiment

Prudence and Persistence: Personality in Student Retention

Student retention is a concern for many higher education institutions and there are many techniques that can be used to increase student retention. Previous research has used student personality data to customize interventions aimed at increasing student success and retention. In this study, prudence levels of incoming students was assessed, and a customized email intervention was designed and administered to students with students having low prudence levels. A variety of outcome measures were used to assess the usefulness of the intervention, including GPA, academic and behavioral citations, and use of campus resources. Results indicate that prudence levels are positively related to GPA and course completion rates. Similarly, the customized email intervention was positively related to GPA, course completion rates, and negatively related to university-issued behavioral citations. The results indicate that prudence levels and customized interventions may be effective for increasing student retention. The meaning and applications of these findings are discussed, and suggestions for future research are outlined