Who is the Perfect Match?

Abstract Using digital tools for teaching allows to unburden teachers from organizational load and even provides qualitative improvements that are not achieved in traditional teaching. Algorithmically supported learning group formation aims at optimizing group composition so that each learner can achieve his or her maximum learning gain and learning groups stay stable and productive. Selecting and weighting relevant criteria for learning group formation is an interdisciplinary challenge. This contribution presents the status quo of algorithmic approaches and respective criteria for learning group formation. Based on this theoretical foundation, we describe an empirical study that investigat…

Contrasting Automatic and Manual Group Formation: A Case Study in a Software Engineering Postgraduate Course

This paper proposes the comparison of a group formation approach based on an evolutionary algorithm with a manual approach performed by an instructor with ten years of experience on this task. The groups were created based on the professional, psychological, and experience profile of each student. The results obtained demonstrated the algorithm’s potential, reaching an average similarity of \(83.46\%\) with the groups formed manually by the instructor.

PeerLA - Assistant for Individual Learning Goals and Self-Regulation Competency Improvement in Online Learning Scenarios

While online learning is already a part of university education and didactics, not all students have the necessary self-regulation competency to really learn on their own efficiently and effectively. In classroom a teacher can take over a moderating part, set intermediate goals and give feedback to one's progress, but participants of online learning courses (e.g. in blended scenarios or Massive Open Online Courses (MOOCs)) face a higher demand of self-regulation competency. This paper presents a course and content independent assistant, PeerLA, which assists in improving self-regulation competency. PeerLA allows setting of long-term goals, breakdown into intermediate goals and keeps track o…

Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model

Predicting student performance as early as possible and analysing to which extent initial student behaviour could lead to failure or success is critical in introductory programming (CS1) courses, for allowing prompt intervention in a move towards alleviating their high failure rate. However, in CS1 performance prediction, there is a serious lack of studies that interpret the predictive model’s decisions. In this sense, we designed a long-term study using very fine-grained log-data of 2056 students, collected from the first two weeks of CS1 courses. We extract features that measure how students deal with deadlines, how they fix errors, how much time they spend programming, and so forth. Subs…

MoodlePeers: Factors Relevant in Learning Group Formation for Improved Learning Outcomes, Satisfaction and Commitment in E-Learning Scenarios Using GroupAL

High-scale and pure online learning scenarios (like MOOCs) as well as blended-learning scenarios offer great possibilities to optimize the composition of learning groups working together on the assigned (or selected) tasks. While the benefits and importance of peer learning for deep learning and improvement of e.g. problem-solving competency and social skills are indisputable, little evidences exist about the relevant factors for group formation and their combination to optimize the learning outcome for all participants (in all groups). Based on the GroupAL algorithm, MoodlePeers proposes an plugin solution for Moodle. Evaluated in a four-week online university mathematics preparation cours…

Daily Fluctuations in Motivation

Abstract. Intrinsic and extrinsic motivation are related to learning success and academic achievement of university students. Process models of self-regulated learning (SRL) suggest that daily academic motivation is affected by study satisfaction on the previous day. In this study, we conducted a secondary analysis of the data by Liborius et al. (2019) , in which the study behavior of a total of 105 students was surveyed daily over 154 days (including both the lecture period and non-lecture period). We tested a mediation model, assuming that SRL components (planning, self-efficacy, time investment, concentration, effort, and procrastination) increase intrinsic motivation and decrease extri…

Mind the Gap!

Abstract. The goal of this study was to investigate the dynamic interplay of affect and time investment during exam preparation using daily learning diaries. University students ( N = 56) reported a simultaneous increase in negative affect as well as intended and actual time investment over the course of the survey period (30 days). Cramming of study time partially accounted for the increase in negative affect. More planning strategies were associated with lower negative and more positive affect. Unmet time schedules predicted higher negative and lower positive affect. Results further revealed compensatory feedback loops: Higher negative affect in the evening predicted higher intended time…

Mentoring styles and novice teachers’ well-being: The role of basic need satisfaction

Abstract School-based mentoring is a key component of support during the challenging teacher induction phase, but different counseling approaches vary in their effectiveness in fostering novices’ well-being. This study investigates effects of two distinct mentoring approaches on emotional exhaustion by considering their potential to address mentees’ basic needs. Data stem from 579 beginning teachers enrolled in the German practical training period. Structural equation modeling indicates that constructivist-oriented mentoring lowers level of exhaustion by supporting mentees’ autonomy need satisfaction. Results do not indicate an effect of transmission-oriented mentoring on mentees’ well-bein…

Inside Self-Regulated Learning

Do Minimal Interventions Increase Participation Rates in Voluntary Online Training at High School?

In preparation for graduating from high school, students face the challenge of having to learn the subject matter of several school years with little guidance. The ability to self-regulate learning is conducive to this. Research has shown that students’ self-regulated learning can be successfully promoted through training. However, when such training is provided voluntarily, not all students participate and dropout rates tend to be high. Minimal interventions on utility value and implementation intention are promising approaches to increase the use of voluntary training. This study investigates whether short interventions can increase the participation in voluntary self-regulated learning …

New ways in fostering self-regulated learning at university: How effective are web-based courses when compared to regular attendance-based courses?

Abstract. Self-regulated learning is essential for studying successfully at university. However, students often show deficits in their ability to learn in a self-regulated way. Consequently, it has become crucial to foster students' self-regulated learning at university. The effectiveness of such courses has primarily been investigated in regular class contexts that require physical attendance. However, web-based course formats are currently gaining in importance. Web-based courses have several advantages (e. g., that students can decide when and where they want to study). The question of whether a web-based course is as effective as an attendance-based one has yet to be answered. In a ran…

What makes a good study day? An intraindividual study on university students’ time investment by means of time-series analyses

Abstract University students often claim to have problems managing the time required to carry out their study demands successfully, which leads to discontent. The question is how much time do students really invest in their studies, what changes occur in time investment over a full academic term, and finally, how is study time related with students' daily study satisfaction? Daily time-series data taken from 105 university students over 154 days were analyzed by means of process analysis techniques and multilevel analysis. The learning time trajectories show a quadratic trend in independent study time and a linear decrease in lecture time. Students' daily study satisfaction was positively r…

Identifying individual differences using log-file analysis: Distributed learning as mediator between conscientiousness and exam grades

Abstract Online learning poses major challenges on students' self-regulated learning. This study investigated the role of learning strategies and individual differences in cognitive abilities, high school GPA and conscientiousness for successful online learning. We used longitudinal log-file data to examine learning strategies of a large cohort (N = 424) of university students taking an online class. Distributed learning, the use of self-tests and a better high school GPA was associated with better exam grades. The positive effect of conscientiousness on exam grades was mediated by distributed learning. Conscientious students distributed their studying over the course of the semester, which…

Deadlines don’t prevent cramming: Course instruction and individual differences predict learning strategy use and exam performance

Abstract The goal of the present study was to investigate how course instruction and individual differences in general academic competences and conscientiousness relate to students' learning strategy use and exam performance. The sample comprised two cohorts of university students who attended a lecture on the same topic, but with varying course instruction: In the blended course (N = 238), the teacher applied deadlines for self-testing and offered regular in-class meetings to encourage distributed practice over the semester. In the online course, students studied independently without regular meetings, nor deadlines (N = 200). Learning strategies were measured objectively using behavioral …

Applying a web-based training to foster self-regulated learning — Effects of an intervention for large numbers of participants

Trainings on self-regulated learning (SRL) have been shown to be effective in improving both competence of self-regulated learning and objective measures of performance. However, human trainers can reach only a limited number of people at a time. Web-based trainings (WBT) could improve efficiency, as they can be distributed to potentially unlimited numbers of participants. We developed a WBT based on the process model of SRL by Schmitz and Wiese (2006) and tested it with 211 university students in a randomized control evaluation study including additional process analyses of learning diaries. Results showed that the training had significant effects on SRL knowledge, SRL behavior measured by…

Effects of Group Formation on Student Satisfaction and Performance: A Field Experiment

This study analyzes the relation of group formation on outcomes of a 4-week online course for prospective students. Group formation was experimentally manipulated based on predefined criteria, personality traits conscientiousness and extraversion. As research questions, groups were considered advantageous if they were formed (a) heterogeneously in extraversion, and (b) homogeneously in conscientiousness. As a result, no uniform outcome was identified. Most variance could be explained on group level, but no significant main effect for experimental grouping was found. Significant interaction between both main effects hint that the results do not provide final answers, but guidance for furthe…