Analysing the Use of Worked Examples and Tutored and Untutored Problem-Solving in a Dispositional Learning Analytics Context

The identification of students’ learning strategies by using multi-modal data that combine trace data with self-report data is the prime aim of this study. Our context is an application of dispositional learning analytics in a large introductory course mathematics and statistics, based on blended learning. Building on previous studies in which we found marked differences in how students use worked examples as a learning strategy, we compare different profiles of learning strategies on learning dispositions and learning outcome. Our results cast a new light on the issue of efficiency of learning by worked examples, tutored and untutored problem-solving: in contexts where students can apply their own preferred learning strategy, we find that learning strategies depend on learning dispositions. As a result, learning dispositions will have a confounding effect when studying the efficiency of worked examples as a learning strategy in an ecologically valid context

Aligning learning design and learning analytics through instructor involvement: a MOOC case study

Producción CientíficaThis paper presents the findings of a mixed-methods research that explored the potentials emerging from aligning learning design (LD) and learning analytics (LA) during the design of a predictive analytics solution and from involving the instructors in the design process. The context was a past massive open online course, where the learner data and the instructors were accessible for posterior analysis and additional data collection. Through a close collaboration with the instructors, the details of the prediction task were identified, such as the target variable to predict and the practical constraints to consider. Two predictive models were built: LD-specific model (with features based on the LD and pedagogical intentions), and a generic model (with cumulative features, not informed by the LD). Although the LD-specific predictive model did not outperform the generic one, some LD-driven features were powerful. The quantity and the power of such features were associated with the degree to which the students acted as guided by the LD and pedagogical intentions. The leading instructor’s opinion about the importance of the learning activities in the LD was compared with the results of the feature importance analysis. This comparison helped identify the problems in the LD. The implications for improving the LD are discussed.Ministerio de Ciencia e Innovación (Proyect grants TIN2017-85179-C3-2-R and TIN2014-53199-C3-2-R)Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. Project VA257P18)European Commission under project grant 588438-EPP-1-2017-1-EL-EPPKA2-KAEuropean Union’s Horizon 2020 under the Marie Sklodowska-Curie grant agreement 79331

Open social student modeling in competency-based education

Ph.D

The Impact of Self-Regulated Learning Interventions on Acting Skills and Self-Regulated Learning

The purpose of this study was to determine the impact of self-regulated learning interventions on acting skills and self-regulated learning. Research questions sought to investigate the impact of self-regulated learning interventions on students’ acting and self-regulated learning skills and determine the perceptions of students regarding the integration of self-regulated learning interventions in the Acting classroom. Self-regulated learning is an important skill for students to have as self-regulated learners are able to self-direct their own learning processes. In the intervention, students engaged in goal setting, progress monitoring, video annotating, and self-evaluation exercises to determine if the self-regulated learning interventions impact their acting or self-regulated learning skills. To conduct this action research, I used a mixed methods research design. Ten students in a rural secondary school Acting class engaged in self-regulated learning interventions, such as goal setting, rehearsals, self-reflection through video annotation of rehearsals, and progress monitoring for a period of six weeks before performing. Data was collected for the intervention using the International Thespian Society – Acting Rubric to assess the impact of the intervention on students’ acting skills and a modified version of the Motivated Scales for Learning Questionnaire (MSLQ-T) to evaluate the impact the intervention on students’ self-regulated learning skills. Participants for the student interviews were selected using purposive sampling specifically, the maximum variation strategy. The two characteristics used to identify interview participants included the quantity of self-regulated learning interventions submitted and the quality of the submissions, as determined using a self-regulated learning intervention rubric (SRI Rubric). Quantitative findings reported students’ acting skills improved significantly throughout the intervention. However, there was no significant impact on students’ self-regulated learning skills, as indicated by the analysis on MSLQ-T. Qualitative findings suggested students perceived the interventions as helpful, but ultimately, students did not engage with the self-regulated learning interventions because they perceived the interventions as repetitive work and an addition to their workload. Students also indicated a lack of self-confidence as a barrier to video annotation integration. Implications of these findings are discussed

Designing and implementing video-based peer feedback tasks to develop communication skills in a Hong Kong higher education institution : An analysis of sociocultural re-mediation through collaborative formative intervention

The use of video-based peer feedback to enhance communication skills is increasingly widespread in higher education, with a growing number of research papers attesting to its importance and impact on learning. Yet whilst existing works evaluate the effectiveness of this approach in terms of learning outcomes and student satisfaction, they do not take sufficient account of the sociocultural aspects that influence the design and implementation of video-based peer feedback activities, or the ways students engage in these activities using video. In this thesis, I investigate how the introduction of a novel video annotation tool into a real setting re-mediates peer feedback practices, in order to highlight sociocultural considerations. To do so, I draw on data from a project in which I used a formative intervention research design to collaborate with instructors in three modules to design and implement tasks where students engage in video-annotated peer feedback on their recorded presentations. Using a theoretical framework based on Engeström’s notion of expansive learning and Scanlon and Issroff’s Activity Theory-derived criteria for evaluating technology in higher education, I analyse interview, survey, annotation and system data from each intervention. I present three reports of how peer feedback was re-mediated, followed by a cross-intervention analysis to illuminate points of commonality and difference. My findings suggest that sociocultural factors were critical in shaping the design and implementation of video-based peer feedback tasks and the ways in which students used the tool to engage in them. Particularly important in each intervention were the extent and nature of instructor facilitation, cognitive scaffolding and social-affective support, and the grading policy. My core contributions are to emphasise the centrality of the instructor’s role in encouraging peer dialogue through structure and guidance, in-class and online; to uncover the relationship between forms of cognitive scaffolding and students’ use of the tool; and to signpost how the negative impact of affective factors on motivation might be mitigated

Analytics of time management strategies in online learning environments: a novel methodological approach

The emergence of technology-supported education, e.g., blended and online, has changed the global higher education landscape. Importantly, the new learning modes involve more complex tasks and challenging ways of learning that require effective time management and strong self-regulation skills. In this regard, one of the most prevalent theoretical lenses to understand learning processes is Self-Regulated Learning (SRL). In reference to SRL models, time is a major resource in learning. The way learners schedule, plan, and enact tactics and strategies on their learning time could tremendously impact their academic achievement. However, the assessment of how learners make time-related decisions in learning is a daunting task, particularly given its latent nature and inherent autonomous learning capacity. One way to address this problem is to make use of unprecedented volumes of data collected by digital learning environments that are precisely timestamped records of actions that learners take while studying. This thesis presents a set of novel learning analytics methods for detecting and understanding time management strategies based on the analysis of digital trace data collected in online learning environments. First, the thesis proposes a new method to detect time management tactics and strategies using a combination of sequence mining and clustering techniques. The thesis also describes how time management tactics and strategies detected with this method are aligned with an SRL model that is used as a theoretical foundation of this thesis. Second, the thesis introduces a novel learning analytics method for the detection of time management tactics and strategies. This method uses a combination of process mining and clustering techniques followed by a complementary process mining technique that has a unique feature to bring insights into the temporal learning processes. This new method also has a strong potential to inform and enhance understanding of how learners make complex decisions about their learning. Third, the thesis investigates mutual connections between time management and learning strategies and their combined connections with academic performance using epistemic network analysis. This analysis provides empirical evidence that supports the proposition that time management is a critical characteristic of effective self-regulated learners. Fourth, the thesis proposes a novel method that integrates computational and visualization techniques to explore the frequency, connections, ordering, and the time of the execution of time management and learning tactics, which usually been done in isolation in the existing literature. Then, the thesis quantitatively and theoretically compare time management and learning strategies detected with this new method to explore the role of time management and learning strategies in learning as drawing on theories of educational psychology. Fifth, this new method was validated in a study that was conducted on the trace data of different learning modalities and interaction modes, where large cohorts are involved. This final study emphasizes the importance of multivocality approach in the study of time management and other relevant learning constructs. Finally, the thesis concludes with a discussion of practical implications, the significance of the results, and future research directions