Scaffolding Reflection: Prompting Social Constructive Metacognitive Activity in Non-Formal Learning

The study explores the effects of three different types of non-adaptive, metacognitive scaffolding on social, constructive metacognitive activity and reflection in groups of non-formal learners. Six triads of non-formal learners were assigned randomly to one of the three scaffolding conditions: structuring, problematising or epistemological. The triads were then asked to collaboratively resolve an ill-structured problem and record their deliberations. Evidence from think-aloud protocols was analysed using conversational and discourse analysis. Findings indicate that epistemological scaffolds produced more social, constructive metacognitive activity than either of the two other scaffolding conditions in all metacognitive activities except for task orientation, as well as higher quality interactions during evaluation and reflection phases. However, participants appeared to be less aware of their activities as forming a strategic, self-regulatory response to the problem. This may indicate that for learning transfer, it may be necessary to employ an adaptive, facilitated reflection on learners' activities

Learning in Uncertainty: Examining the Relationship Between Perceived Environmental Uncertainty and Self-Regulated Learning of Finance Professionals, and The Role of Technology in Supporting It

Uncertainty is an inherent component of the modern-day workplace. Professionals need to learn to navigate their work lives through these uncertainties. Thus, learning to manage continuous change and uncertainty is key to professionals carrying out their practice successfully. Although past research has sought to unpack the intricacies of uncertainty perception and management, it has been predominantly at an organisational level. Two factors remain largely unexplored in the current literature: 1) Uncertainty perception and learning at an individual level and 2) Role of technology in supporting individual learning during uncertainty. The research questions posed in this thesis, stem from an inclination to address this gap and evaluate whether empirical evidence exists for an association between perception of uncertainty and how individuals learn during periods of uncertainty, and the role of technology in mediating this association. This thesis aims to address the following research questions through a mixed methods research design, including semi-structured interviews, questionnaires, and co-design approach with members from the Chartered Institute for Securities and Investments (CISI). What is the nature of environmental uncertainties within the finance sector and the perception of finance professionals towards these uncertainties? How do finance professionals self-regulate their learning in times of uncertainty? How do finance professionals perceive the role of technology in supporting their self-regulated learning during uncertainty? How do finance professionals perceive the usefulness of the LiU framework in recommending SRL strategies based on the type of perceived uncertainty? Three studies were planned to answer these research questions. Study 1 focused on delineating the nature and sources of environmental uncertainties in the finance sector. Results from the thematic analysis of interviews from Study 1 (n = 9) provided the categorisation of sources of objective uncertainty within the finance sector. It also provided insights into how finance professionals perceived the antecedents and consequences of uncertainty and what type of self-regulated learning strategies they used when faced with uncertain times. Whether their self-regulation strategies differed based on the type of uncertainty they perceived was investigated in Study 2. Study 2 investigated the relationship between self-regulated learning and perceived environmental uncertainty using the quantitative survey method and secondary analysis of interview data. Statistical analysis of survey data (n = 39) revealed that certain self-regulated learning strategies were significantly different across the types of perceived uncertainties. Among the self-regulation phases, statistically significant differences were seen in forethought and self-reflection phases; however, no significant differences were found in the performance phase based on the type of perceived uncertainty. This means that the way professionals planned their learning activities, set goals to achieve the learning objective and the extent to which they valued the learning activity depended on the type of uncertainty they perceived. Similarly, their self-reflective learning processes also differed based on the type of perceived uncertainty. However, the wide range of strategies they undertook to achieve the learning goals, their critical thinking, and help-seeking abilities were the same throughout, without a differential effect of perceived uncertainty. These results were in alignment with the thematic analysis of secondary interview data (n = 26), where the SRL strategies were associated with the type of perceived uncertainty. Study 3 investigated the role of technology in supporting the self-regulated learning behaviour of professionals using a co-design approach with two iterative cycles (Iteration 1: n=10, Iteration 2: n=10). Results from Study 3 showed that of the three phases of learning in uncertainty (identify- introspect-implement), any technology support was most effective in the introspection phase. It also revealed the importance of reflection as a dominant theme when learning in uncertainty. Altogether, the original contribution of this thesis was an examination of the relationship between perceived environmental uncertainty and self-regulated learning and the role of technology in supporting it. In doing so, it highlighted the importance of guiding the professionals in the regulation of their learning and the positive implications it had in terms of motivational and metacognitive aspects. It also highlighted the role of a technological scaffold in helping the professionals become more reflective in their learning and strategic in managing their uncertainty

Evolutionary Clustering of Apprentices' Self- Regulated Learning Behavior in Learning Journals

Learning journals are increasingly used in vocational education to foster self-regulated learning and reflective learning practices. However, for many apprentices, documenting working experiences is a difficult task. In this article, we profile apprentices' learning behavior in an online learning journal. Based on a pedagogical framework, we propose a novel multistep clustering pipeline that integrates different learning dimensions into a combined profile. Specifically, the profiles are described in terms of effort, consistency, regularity, help-seeking behavior, and quality of the written entries. Our results on two populations of chef apprentices (183 apprentices) interacting with an online learning journal (over 121K entries) show that our pipeline captures changes in learning patterns over time and yields interpretable profiles that can be related to academic performance. The obtained profiles can be used as a basis for personalized interventions, with the ultimate goal of improving the apprentices' learning experience

Assessment, development and experimental evaluation of self-regulatory support in online learning

Online learning requires a higher level of self-regulation than face-to-face learning. Learners are likely to differ in their cognitive, metacognitive, affective or motivational resources to meet this demand. Individual differences in self-regulation is one major factor contributing to success or failure in online learning, other factors include characteristics of the online learning environment and the complexity of the learning content itself. Lack of self-regulation is likely to affect learners’ engagement with the course content, may result in sub-optimal learning outcomes, including failure to complete the course. A virtual learning assistant has been designed and developed to support online learners. This research aims at ascertaining the effectiveness of providing adaptive assistance in terms of (a) compensatory and (b) developmental effects. Online learners involved in the empirical part of this study (N = 157) were randomised into one of two experimental conditions. For the intervention group, the online learning assistant provided personalised in-browser notifications. This feature was disabled for the learners in the control condition. Results indicate that the adaptive assistance did not result in noticeable developmental shifts in learners’ self-regulation as assessed via conventional self-report measures. However, learners allocated to the intervention group spent less time online per day in first three weeks of being exposed to the adaptive assistance, reduced their time commitment to entertainment websites during first two weeks, and increased their engagement with educational web resources during the first ten days. In addition to the time-varying effects, these compensatory (behavioural) shifts were moderated by learners’ individual differences in personality. The outcome of this study suggests that the utilisation of a virtual learning assistant that provides adaptive assistance can be effective in compensating for not yet developed self-regulatory skills, and subsequently help facilitating success in learning on short online courses