A series of Massive Open Online Courses (MOOCs) in the Curriculum and Instruction (CUIN) Department at a university are collaboratively being designed and developed by a team of doctoral students ...with mentorship from two CUIN professors. The first two MOOCs, Powerful Tools for Teaching and Learning: Digital Storytelling MOOC (DS MOOC) and Powerful Tools for Teaching and Learning: Web 2.0 Tools, have been developed and offered multiple times on the Coursera platform. This paper reports on the relationships between learners' patterns and motives of engagement and their prior subject knowledge with their course performance in the Digital Storytelling MOOC. Results from this study indicate that learners who demonstrated active engagement in the MOOC tended to outperform other learners who did not practice this trait. Learners whose motives for participation involved earning the Continuing Professional Development certificate, gaining skills, ideas and inspirations, and improving their professional practice outperformed the students who valued these traits less. Learners who possessed moderate level of content knowledge seemed to benefit most from the course. This paper contributes insight into aspects of students’ behaviors that possibly contributed to their success in a MOOC and invites discussion on how to reinforce these traits.
•Active groups of learners outperformed in the MOOC compared to the other groups.•Learners with moderate prior content knowledge benefitted most from the course.•Different motives for participation result in different course performance.
Massive Open Online Course (MOOC) platforms capture the digital traces of millions of learners and generate an avalanche of “numbers” on learner behavior in MOOCs. Yet little is known about the ...dynamics through which MOOCs can support individual learning as the cognitive and social constituents of this complex process and their interplay within this process do not clearly surface in this large mass of “numbers”. This study analyzed the content generated by learners in a MOOC discussion forum with a particular focus on the still under-explored cognitive dimension of learning in MOOCs and demonstrated how certain levels of cognitive engagement relate to learning. It further examined the interplay between the cognitive and social aspects, revealing the moderating role of the social aspect in the association between the lowest level of cognitive engagement and learning in a MOOC environment. The study concludes with discussing the theoretical and practical implications of the findings and with highlighting the need to consider the interdependencies between the cognitive and social variables and learning when designing and evaluating MOOCs.
•Forum posts reflect the level of cognitive engagement in content and have a complex relationship with performance in a MOOC.•Lowest level of cognitive engagement in MOOC forums has a significant negative association with MOOC performance.•The social aspect of MOOC forums moderates the relationship between the lowest level of cognitive engagement and learning.•Analysis of the interplay of cognitive and social aspects of forums enhances understanding of how MOOCs support learning.
We examined students’ naturalistic decisions about spacing their study in an undergraduate course (N = 185) and whether self-selected spacing predicted course performance. Usage of two study tools – ...an online textbook and quiz tool – was recorded daily. We operationalized spacing as how often the tools were used and the timing of their use relative to exams. We found that students increased their study near deadlines and exams, used the textbook more often than the quiz tool, and used the tools infrequently when they were optional (vs. required). Importantly, spaced retrieval practice (via quiz tool) predicted course performance and GPA, whereas spaced reading (via textbook) was a weaker predictor. That is, when students opted for more frequent and early quizzing, they earned higher grades, even controlling for time spent quizzing. Thus, self-selected spaced study – especially spaced retrieval practice – supports student achievement.
•We examined college students' decisions about spacing their study using behavioral trace data.•We operationalized spacing as the frequency and timing of students' use of online study tools.•Many students did not use the study tools when they were optional (vs. required).•Greater spacing of study was associated with higher course performance and GPA.•Spaced retrieval practice predicted grades more strongly than spaced reading did.
The limited instructional support in Massive Open Online Courses (MOOCs) inherently demands learners to self-regulate their learning. MOOC research shows that learners are more successful when they ...engage in self-regulated learning (SRL) behaviors such as planning what to study and reviewing study materials. However, many learners struggle with SRL. In this study, we examined the effect of two types of SRL prompts (i.e., questions or a combination of questions and recommendations) on SRL activities, course engagement, and performance in MOOCs. Learners either received questions supporting SRL, questions supporting SRL followed by recommendations, or neither questions supporting SRL nor recommendations. Log data was used to examine learners’ behavior in the MOOCs. Results showed the SRL prompts, in general, are effective in enhancing SRL-related activities and course engagement. However, the effectiveness of the SRL prompts may be influenced by the complexity of the MOOCs. The current study adds to the field of SRL by examining prompting as an approach to enhance SRL in MOOCs.
•Prompts supporting self-regulated learning (SRL) were examined in MOOCs.•SRL prompts are especially beneficial for learners in more complex MOOCs.•Prompted learners completed more course items on time indicative of time-management.•No significant effect was found for SRL activities indicative of self-monitoring.•Log file analysis and process mining provide insight in SRL-related behavior.
This study examines the effects that online collaborative note-taking has on student performance. The study draws on 10 weeks of data from 273 STEM university students who were collaborating in 61 ...groups. Group and individual learning were assessed weekly by evaluating the completeness of collaborative note-taking documents and subsequent individual assessments. Analysis suggested up to 23% of the variation in course performance could be attributed to between-group effects. Further, a series of 10 multilevel temporal models suggested no substantive effects in the first half of the course, though in the second half of the course, groups that co-created more complete course notes tended to exhibit improved average student performance. We speculate that the learning advantages afforded to student groups that produce more complete course notes may be delayed. This study adds to the growing body of research into the effects that collaboration has on student learning.
•Collaborative learning behaviors impact the quality of note-taking completeness.•Collaborative learning behaviors have some limited impact on student performance.•Note-taking completeness has some limited impact on student performance.•The impact of collaborative behaviors and note-taking completeness increases as groups collaborate together longer.
Collaborative learning (CL) is a common teaching strategy in colleges that involves actively working in groups to achieve a goal. Several studies and theories endorse it as contributing to students’ ...achievement, motivation, and higher-order thinking skills. However, these studies are inconsistent in the way they define and operationalize CL. For example, they do not separate the quantity and the quality of CL, nor do they distinguish between course-specific and general attitudes toward CL. The study suggests that researchers should define CL more precisely, and demonstrates this approach using a case study (N = 38). This study examines whether the quality and quantity of group work predicted course achievement after controlling for prior achievement, individual-level motivation, and social ties among students. Quality of CL was operationalized as positive attitudes toward CL in the current course and in general, and quantity of CL was operationalized as the frequency of interactions among group members. Social ties were measured using Social Network Analysis (SNA) which allows researchers to identify the number and strength of connections among students. Findings suggest that positive attitudes toward CL in the current course predicted higher achievement levels, but the frequency of interactions and positive attitudes toward CL in general were associated with lower achievement levels. That is, in the current context, course-specific quality of CL was positively associated with achievement, but other ways of operationalizing CL were not, and in fact had negative relationships with achievement. The study also demonstrates the use of SNA when exploring students’ relationships; it shows that they were associated with course performance but that this association diminished after controlling for students’ attitudes. Overall, it is recommended that researchers clarify what they intend to measure when exploring CL, as this can have an important impact on findings.
We examine Emotional Intelligence (EI) as a predictor of academic performance in business school leadership coursework. Leadership requires competent interaction with subordinates on an interpersonal ...level. This requires interpersonal skills, such as engaging in difficult conversations. We argue that performance in a course that develops these skills is facilitated by EI. We report data from two studies (Study 1 N = 609; Study 2 N = 529) in which students completed a battery of both self-reported and ability-tested EI measures. Controlling for cognitive ability and personality, ability-tested EI predicted leadership course grades in both studies, whereas self-reported EI did not do so in either. Each of the ability EI constructs tested—namely emotion perception, emotional understanding, emotion management, and emotion attention regulation—significantly predicted course performance. These findings suggest information about ability EI can lead to understanding who stands to benefit most from leadership education and for students to be more accurate in their self-assessments about their emotional abilities.
This paper explores how to effectively predict and analyze students’ Civics course grades and their correlation with students’ behaviors based on the integrated transfer learning strategy to improve ...the teaching quality of Civics courses for college students through the integrated transfer learning strategy. The feature engineering method is used to extract the achievement features, and the achievement analysis and prediction model is established by Stacking integrated learning method combined with various algorithms such as KNN, linear regression and decision tree. By predicting and analyzing the Civics grades of college A students, the results show that the average error between the expected grades and the measured grades of computer science majors is 4.00 points. In contrast, biological science majors underestimate it by 5.41%. In addition, the cluster analysis of students’ behaviors using the k-mediods algorithm revealed significant differences between students with excellent academic performance and those with poorer performance in behaviors such as frequency of consumption and number of books borrowed. The integrated transfer learning strategy has a better application effect in the prediction and analysis of the performance of the Civics course, which can provide a powerful support to improve the quality of teaching.
Many universities offer courses in which students from various disciplines form teams to work on complex design challenges. Despite the importance of such teams for engineering design education, very ...little is known about them. This study explores the impact of graduate student goal orientations (mastery, performance-proof, and performance-avoidance) on course performance (team performance and peer assessment) via functional team member selection. The study examined 122 teams and found that students with performance-proof and performance-avoidance orientations are more likely to form functionally homogenous teams. However, there is no significant relationship between a mastery goal orientation and functional team diversity. Furthermore, the results indicate that functional team diversity is a double-edged sword for course performance, insofar as it has a positive impact on team performance, but also a negative effect on peer assessment. In addition, both performance goal orientations (performance-proof and performance-avoidance) have a negative effect via functional diversity on team performance and a positive effect on peer assessment. The findings advance our understanding of team member selection by graduate students and the effect thereof on course performance. Hence they may assist in developing future tools and processes to enhance learning by engineering design students in interdisciplinary design projects.
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