Internet and Higher Education最新文献

The aim of this study was to examine how motivation, perceived learning support, learning engagement, and self-regulated learning strategies relate to learners' perceived learning outcomes of massive open online courses (MOOCs). An online survey was administered to 546 participants from four MOOCs. Seven types of reasons for attending MOOCs were identified, ranging from intrinsic to extrinsic motivation. One-way MANOVA revealed that learners with autonomous motivation demonstrate higher scores on perceived learning outcomes than learners with controlled motivation. In addition, multiple regression analysis methods showed that course design, interaction with instructors and peers, engagement in learning activities, and applying cognitive and metacognitive learning strategies significantly explain differences in perceived learning outcomes. Furthermore, mediation analyses demonstrated that cognitive and metacognitive learning strategies significantly mediated the relationships between motivation, perceived learning support, and learning engagement on the one hand and perceived learning outcomes on the other. Finally, practical implications are discussed and future research directions are recommended.

The main purposes of this study were, first, to identify Taiwanese university students’ online academic help-seeking (OAHS) patterns and further to compare their Internet self-efficacy (ISE) among the identified patterns. A total of 366 Taiwanese university students were invited to fill out two questionnaires to understand their OAHS and ISE, respectively. The results revealed that three OAHS patterns, adaptive, self-reliant, and socially-affiliated, were characterized based on the cluster analysis. The differences in the students’ various ISE dimensions among the three patterns were then compared. The adaptive students, who commonly adopted all types of OAHS behaviors, tended to be the most efficacious in the seven measured ISE dimensions. The self-reliant students, highlighting that they mainly sought help by searching for relevant information online, showed higher confidence in the ISE dimensions of “Usage,” “Application,” and “Learning” than did the socially-affiliated students (i.e., those who tended to use formal and informal queries to seek academic help online). The socially-affiliated students only showed higher confidence in sharing online information than the self-reliant students. However, in the “Communication,” “Verifying,” and “Metacognition” ISE dimensions, there were no significant differences between the socially-affiliated and self-reliant students.

The overarching goal of this design-based research is to develop and evaluate a set of design principles for a fully online flipped classroom to support students' learning outcomes, behavioural, emotional, and cognitive engagement. In a fully online flipped classroom, students are encouraged to complete online pre-class activities asynchronously. But unlike in the conventional flipped approach, students do not subsequently meet face-to-face in classrooms, but rather online synchronously. The testbed involved a conventional flipped class (Cycle 0), a fully online flipped class (Cycle 1), and a refined fully online flipped class (Cycle 2). The results showed that although all three groups of students performed equally well in learning, the refined online flipped model was more effective in supporting students' behavioural engagement in the synchronous online class sessions than the online flipped model. This study contributes to the extant literature by explicating the design principles that support student engagement in fully online flipped learning.

Learning programming is difficult, and many students fail or have poor outcomes. To learn to program means to master steps in the complex problem-solving activity. Previous research uncovered a rich set of domain-specific and generic cognitive and metacognitive strategies students use when they learn to program. The processes that problem-solving experts demonstrate are very similar to those studied by self-regulated learning researchers. This study proposes Self-Regulated Learning (SRL) process types derived from the SRL phases indicators developed from log data captured from students' interaction with the instructional scaffold for programming assignments in LMS. The process types were defined from theoretical and pragmatic perspectives, with the aim to indicate concrete interventions for improving problemsolving skills. We have observed and quantified students' use of the SRL processes of distinct types in the series of five problem-solving assignments. We have also observed the progression of SRL processes used by each student in the assignments. Our modelling showed that students with domain knowledge at the same level achieve higher assignment marks when they demonstrate SRL processes at the higher level; importantly, students with the lowest programming skills benefit the most.

Bichronous Online Learning is the blending of asynchronous and synchronous online learning. In this qualitative study, 12 award-winning online instructors were interviewed for their online teaching practices focused on blending, design, facilitation, and assessment of asynchronous and synchronous online modalities. Data was collected through virtual interviews which were recorded, transcribed and analyzed. Award-winning instructor practices of blending are discussed through their blending decisions, sequences, and models. Instructors shared their decisions related to blending, such as modality purposes, affordances, and required or optional synchronous sessions. Blending sequences that emerged were asynchronous followed by synchronous, asynchronous followed by synchronous and then asynchronous again. Blending models that resulted were the complement model, replacement model and enhancement model. Asynchronous and synchronous design, facilitation and assessment strategies used by the award-winning online instructors are discussed in detail. The findings have implications for online instructors, students, instructional designers and administrators.

Credit hours traditionally quantify expected instructional time per week in a course, informing student course selection decisions and contributing to degree requirement satisfaction. In this study, we investigate course load measures beyond this metric, including determinants from course assignment structure and LMS interactions. Collecting 596 course load ratings on time load, mental effort, and psychological stress, we investigate to what extent course design decisions gleaned from LMS data explain students’ perception of course load. We find that credit hours alone explain little variance compared to LMS features, specifically number of assignments and course drop ratios late in the semester. Student-level features (e.g., satisfied prerequisites and course GPA) exhibited stronger associations with course load than the credit hours of a course; however, they added only little explained variance when combined with LMS features. We analyze students’ perceived importance and manageability of course load dimensions and argue in favor of adopting a construct of course load more holistic than credit hours.

Social presence is a key element in collaborative/cooperative learning. In online learning environments, it is challenging to measure the current state of social presence. This work aims to identify measures of social presence.

We manually coded 3546 students' postings (n = 49 students). We selected measures from social network analysis and indices derived from log data as potential indicators. We conducted an exploratory path analysis to define which indicators appropriately describe social presence.

The size of the individual egocentric student's network (path coefficient = −0.56**) and constraint (path coefficient = −0.51**), as well as the number of forums in which students were active (path coefficient = 0.49**) and the number of solved learning activities (path coefficient = −0.59**) were indicators of the level of social presence.

We were able to identify four indicators for social presence in online-based courses readily available within routine data from learning management systems. We will focus now on how social presence in an ongoing course develops.

This study examined learning processes in undergraduate online general chemistry courses. The study aimed to characterize learners according to their learning patterns and to identify indicators that predict students' success in an online environment. Specifically, we focused on the role of a central factor affecting success in online courses: self-regulated learning and learner engagement. To this end, we used a mixed methods approach that combines semi-structured interviews and statistical analysis. We applied two logistic regression models and a decision tree algorithm and found two parameters that can predict completion of the course: the submission status of an optional assignment and the students' cumulative video opening pattern (SCOP). Recommendations for institutions and lecturers regarding the benefits of implementing these models to identify self-regulated learning patterns in online courses and to design future effective interventions are discussed. Regarding students, we emphasize the importance of time management and how choices they make with respect to their learning process affect their potential for success.

The inclusion of game-based learning in tertiary institutions is increasing as educators seek ways to enhance student engagement and motivation. During the development process for gaming resources, educators need feedback to ensure a quality learning experience. In many cases this feedback is generally received from students at the end of the subject or course and is often regulated centrally. Another way of garnering feedback and capturing player analytics could be to capitalize on the millions of global gamers. A game developed for use in a Health Sciences and Medicine program, The King's Request: Physiology and Anatomy Revision Game, was made freely available on the Steam platform. Over 16,000 Steam users engaged with the game over 12 months, with 150 providing written reviews. In contrast, a cohort of 100 first-year health science and medical students were requested to review the game after playing in class, with only 17 providing written feedback. In reviewing feedback, similarities were found between the groups, such as where both Steam community players and in-class students requested more questions and a longer game. However, the Steam community highlighted several unique aspects which could be used to improve the game for learning, such as a refined implementation of the incentive system. As the online gaming community is far larger than students enrolled in any tertiary subject, its expansive feedback can be used to accelerate the design and refinement of serious games. This wealth of feedback could provide unique insights for educators wishing to improve the provision of games in education and the overall student learning experience.

E-learning use indicates the success of implementing e-learning environments since it plays a key role in mediating drivers for goal achievement. The motivation for e-learning use greatly depends on developing effective e-learning processes. Two particular issues, technology use and constructivist learning, are proposed for further defining three key determinants, technology affordances, e-content interaction, and e-social interaction, as the determinants of e-learning use, and in turn, academic performance. The three determinants for their integration are unique for a special guide to effective e-learning design. Learner involvement is an emotional moderator for an interactive role with e-learning use. An existing e-learning environment with learning experience is used to collect both subjective and objective data. Technology affordances and e-content interaction have important influence on e-learning use, whereas e-social interaction does not. E-learning use also indicates the importance as a key mediator to achieve academic performance. Learner involvement shows insignificance with the moderating role. These findings have important implications for developing new learning approaches and effective e-learning processes, in particular, the insignificance of e-social interaction and learner involvement.