This paper describes a study that looked at the effects of different technology-use profiles on educational experience within communities of inquiry, and how they are related to the students' levels ...of cognitive presence in asynchronous online discussions. Through clustering of students (N=81) in a graduate distance education engineering course, we identified six different profiles: 1) task-focused users, 2) content-focused no-users, 3) no-users, 4) highly intensive users, 5) content-focused intensive users, and 6) socially-focused intensive users. Identified profiles significantly differ in terms of their use of learning platform and their levels of cognitive presence, with large effect sizes of 0.54 and 0.19 multivariate η2, respectively. Given that several profiles are associated with higher levels of cognitive presence, our results suggest multiple ways for students to be successful within communities of inquiry. Our results also emphasize a need for a different instructional support and pedagogical interventions for different technology-use profiles.
•We investigated technology-use profiles using six offerings of a graduate level course with the total of 81 students.•Our MANOVA results revealed six technology-use profiles, associated with different levels of cognitive presence.•Building on the previous research we describe identified clusters and discuss the impact of our findings.
Contemporary literature on online and distance education almost unequivocally argues for the importance of interactions in online learning settings. Nevertheless, the relationship between different ...types of interactions and learning outcomes is rather complex. Analyzing 204 offerings of 29 courses, over the period of six years, this study aimed at expanding the current understanding of the nature of this relationship. Specifically, with the use of trace data about interactions and utilizing the multilevel linear mixed modeling techniques, the study examined whether frequency and duration of student–student, student–instructor, student–system, and student–content interactions had an effect of learning outcomes, measured as final course grades. The findings show that the time spent on student–system interactions had a consistent and positive effect on the learning outcome, while the quantity of student–content interactions was negatively associated with the final course grades. The study also showed the importance of the educational level and the context of individual courses for the interaction types supported. Our findings further confirmed the potential of the use of trace data and learning analytics for studying learning and teaching in online settings. However, further research should account for various qualitative aspects of the interactions used while learning, different pedagogical/media features, as well as for the course design and delivery conditions in order to better explain the association between interaction types and the learning achievement. Finally, the results might imply the need for the development of the institutional and program-level strategies for learning and teaching that would promote effective pedagogical approaches to designing and guiding interactions in online and distance learning settings.
•We examined the relationship between interaction types and learning out-come.•The findings show significant positive effect of student–system interactions.•Student-content interactions were negatively associated with the learning outcome.•Educational level and course context are important for interaction types supported.
This paper describes a study that looked at the effects of different teaching presence approaches in communities of inquiry, and ways in which student–student online discussions with high levels of ...cognitive presence can be designed. Specifically, this paper proposes that high-levels of cognitive presence can be facilitated in online courses, based on the community of inquiry model, by building upon existing research in i) self-regulated learning through externally-facilitated regulation scaffolding and ii) computer-supported collaborative learning through role assignment. We conducted a quasi-experimental study in a fully-online course (N=82) using six offerings of the course. After performing a quantitative content analysis of online discussion transcripts, a multilevel linear modeling analysis showed the significant positive effects of both externally-facilitated regulation scaffolding and role assignment on the level of cognitive presence. Specifically, the results showed that externally-facilitated regulation scaffolding had a higher effect on cognitive presence than extrinsically induced motivation through grades. The results showed the effectiveness of role assignment to facilitate a high-level of cognitive presence. More importantly, the results showed a significant effect of the interaction between externally-facilitated regulation scaffolding and role assignment on cognitive presence. The paper concludes with a discussion of practical and theoretical implications.
•Externally-facilitated regulated (EFR) learning and role scripts for online discussions•Design-based study conducted in a fully-online master's level course•Multi-level linear modeling showed significant effects of EFR and role scripting.•Motivation needs to be complemented with EFR for high level of cognitive presence.•EFR can offer equitable opportunities for cognitive presence of different roles.
Recent developments in educational technologies have provided a viable solution to the challenges associated with scaling personalised feedback to students. However, there is currently little ...empirical evidence about the impact such scaled feedback has on student learning progress and study behaviour. This paper presents the findings of a study that looked at the impact of a learning analytics (LA)-based feedback system on students' self-regulated learning and academic achievement in a large, first-year undergraduate course. Using the COPES model of self-regulated learning (SRL), we analysed the learning operations of students, by way of log data from the learning management system and e-book, as well as the products of SRL, namely, performance on course assessments, from three years of course offerings. The latest course offering involved an intervention condition that made use of an educational technology to provide LA-based process feedback. Propensity score matching was employed to match a control group to the student cohort enrolled in the latest course offering, creating two equal-sized groups of students who received the feedback (the experimental group) and those who did not (the control group). Growth mixture modelling and mixed between-within ANOVA were also employed to identify differences in the patterns of online self-regulated learning operations over the course of the semester. The results showed that the experimental group showed significantly different patterns in their learning operations and performed better in terms of final grades. Moreover, there was no difference in the effect of feedback on final grades among students with different prior academic achievement scores, indicating that the LA-based feedback deployed in this course is able to support students’ learning, regardless of prior academic standing.
•A learning analytics-based system was used to deliver process feedback to students in a course.•The learning-analytics feedback employed multimodal data, such as log data from the learning management system and e-book.•The pattern of self-regulated learning differed between students who had received the feedback, and those who had not.•Final course marks were significantly higher for students who had received the feedback, compared to those who had not.•There was no difference in impact of the LA-based, process feedback among students with different program entry scores.
Existing studies have shed light on policies and strategies for learning analytics (LA) adoption, yet there is limited understanding of associations among factors that influence adoption processes or ...the change in priorities when institutional experience with LA increases. This paper addresses this gap by presenting a study based on interviews with institutional leaders from 27 European higher education institutions. Results showed that experienced institutions demonstrated more interest in exploring learning behaviour and pedagogical reformation than simply measuring a phenomenon. Experienced institutions also paid more attention to methodological approaches to LA than data constraints, and demonstrated a broader involvement of teachers and students. This paper also identifies inter-related connections between prevailing challenges that impede the scaling of LA. Based on the results, we suggest regular evaluations of LA adoption to ensure the alignment of strategy and desired changes. We also identify three areas that require particular attention when forming short-term goals for LA at different phases of adoption
•Connections of key adoption factors vary among institutions with different LA experience.•Experienced institutions prioritised exploring over measuring a learning phenomenon.•Experienced institutions were more concerned with methods than constraints of data.•Experienced institutions engaged primary stakeholders more equally.•Special attention is need for institutional context, people issues, and ethics and privacy.
Student-facing visualisations have attracted increased attention with recent developments in data-driven tools to support individual and group work. Learning analytics dashboards (LADs), a ...data-enhanced feedback tool that allows students to make sense of their learning by providing insights into their learning behaviours represents one of the prominent examples of this trend. While these visualisation tools are increasingly used to study and enhance students' learning in academic contexts, current research is limited regarding the effects of the LADs in K-12 environments. There is a missed opportunity to empower teams and allow instructors and researchers to understand how teams use the LAD to regulate their learning. In this study, we developed a K-12 LAD for supporting students' collaborative work and evaluated with respect to students' perceived usefulness of the proposed LAD and the association between its use and course performance. The study followed a mixed-methods approach, combining quantitative analysis of log data from the dashboard and qualitative analysis of students’ perceptions using surveys and focus groups. Our results show that different roles within teams have distinguished engagement patterns with the LAD and that the tool improves the collaborative learning experience. We postulate that the implications of this study will aid future research work when investigating the behaviours of teams and optimising their learning using LADs.
•Learning analytics dashboard in K-12 collaborative learning promotes engagement and collaboration.•Team interactions with a dashboard can support instructors in assessing and improving collaborative learning behaviours.•Visuals illustrating workflow processes of teams fosters more engagement with the dashboard compared to traditional visuals.•Discovered behavioural differences between team members and leader engagement with the learning analytics dashboard.•K-12 teams perceived the learning analytics dashboard as useful in supporting team regulation in collaborative settings.
Abstract Team cohesion is critical in driving successful outcomes for teams in collaborative learning settings. It shapes team behaviour, fostering shared perceptions, group synchrony and a common ...goal-oriented approach. This affinity becomes evident in dynamic interactions, offering insights into team behaviour through interaction data analysis. Interpreting interaction data proves complex, hampering our understanding and insights into shared team perceptions and task cohesion development. This paper used temporal motif analysis to examine the changes in team members’ cohesive perceptions and behaviours, including task cohesion, performance outcomes, engagement and group synchrony. Trace data from an online work-integrated learning environment captured learning behaviours, while responses to a questionnaire at different stages of a study program captured task cohesion and cohesive perceptions. The findings reveal teams with strong task cohesion and high performance tend to share similar cohesive perceptions driven by interdependent interactions. Conversely, teams with different cohesion perceptions have lower interaction interdependence and poorer performance. Through analysing team interaction data, this study uncovered key insights to promote positive adjustments aligning team perceptions, enhancing collaborative learning and offering support for improved performance, engagement and synchrony among teams, ultimately benefiting learning outcomes and the cultivation of skills and competencies.
One of the striking differences between massive open online courses (MOOCs) and previous innovations in the education technology field is the unprecedented interest and involvement of the general ...public. As MOOCs address pressing problems in higher education and the broader educational practice, awareness of the general public debate around MOOCs is essential. Understanding the public discourse around MOOCs can provide insights into important social and public problems, thus enabling the MOOC research community to better focus their research endeavors. While there have been some reports looking at the state of the MOOC‐related research, the analysis of the public debate surrounding MOOCs is still largely missing. In this paper, we present the results of a study that looked at the content of the public discourse related to MOOCs. We identified the most important themes and topics in MOOC‐related mainstream news reports. Our results indicate that coverage of MOOCs in public media is rapidly decreasing: by the middle of 2014, it decreased by almost 50% from the highest activity during 2013. In addition, the focus of those discussions is also changing. While the majority of discussions during 2012 and 2013 were focused on MOOC providers, the announcements of their partnerships, and million dollar investments, the current focus of MOOC discourse seems to be moving toward more productive topics focused on the overall position of MOOCs in the global educational landscape. Among different topics that this study discovered, government‐related issues and the use of data and analytics are some of the topics that seem to be growing in popularity during the first half of 2014.
This paper examines the discrete learning strategies employed within a massive open online course and their relationship to the student learning experience. The theoretical framework centered on the ...Community of Inquiry model of online education, which outlines the three critical dimensions (presences) of student learning experience: teaching, social, and cognitive presence. The Community of Inquiry survey instrument, administered as the part of the post-course survey, was used to measure student perceived levels of the three presences. Cluster analysis revealed three different groups of students with unique study strategies: limited users, selective users, and broad users. The strategies adopted significantly differed in student use of available tools and resources, final course grade, as well as the perceived levels of cognitive presence. The results also indicate there were significant differences regarding student commitment to learning, motivations and goals for enrolling in a MOOC, as well as goal orientation, approaches to learning, and the use of different study strategies. Implications for research and practice of online learning are further discussed.
•We examined student study strategies within MOOCs based on interaction log data.•Cluster analysis revealed three groups: limited, selective, and broad users.•Differences in final grades and pre- and post-course surveys answers were examined.•We observed differences in final grades and perceived levels of cognitive presence.•We observed differences across factors such as motivation and goal orientation.
The field of learning analytics was founded with the goal to harness vast amounts of data about learning collected by the extensive use of technology. After the early formation, the field has now ...entered the next phase of maturation with a growing community who has an evident impact on research, practice, policy, and decision-making. Although learning analytics is a bricolage field borrowing from many related other disciplines, there is still no systematised model that shows how these different disciplines are pieced together. Existing models and frameworks of learning analytics are valuable in identifying elements and processes of learning analytics, but they insufficiently elaborate on the links with foundational disciplines. With this in mind, this paper proposes a consolidated model of the field of research and practice that is composed of three mutually connected dimensions - theory, design, and data science. The paper defines why and how each of the three dimensions along with their mutual relations is critical for research and practice of learning analytics. Finally, the paper stresses the importance of multi-perspective approaches to learning analytics based on its three core dimensions for a healthy development of the field and a sustainable impact on research and practice.
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