A Multilevel Analysis of the Effect of Prompting Self-Regulation in Technology-Delivered Instruction

We used a within-subjects design and multilevel modeling in two studies to examine the effect of prompting self-regulation, an intervention designed to improve learning from technology-delivered instruction. The results of two studies indicate trainees who were prompted to self-regulate gradually improved their knowledge and performance over time, relative to the control condition. In addition, Study 2 demonstrated that trainees’ cognitive ability and self-efficacy moderated the effect of the prompts. Prompting self-regulation resulted in stronger learning gains over time for trainees with higher ability or higher self-efficacy. Overall, the two studies demonstrate that prompting self-regulation had a gradual, positive effect on learning, and the strength of the effect increased as trainees progressed through training. The results are consistent with theory suggesting self-regulation is a cyclical process that has a gradual effect on learning and highlight the importance of using a within-subjects design in self-regulation. research

Active Learning: Effects of Core Training Design Elements on Self-Regulatory Processes, Learning, and Adaptability

This research describes a comprehensive examination of the cognitive, motivational, and emotional processes underlying active learning approaches, their effects on learning and transfer, and the core training design elements (exploration, training frame, emotion-control) and individual differences (cognitive ability, trait goal orientation, trait anxiety) that shape these processes. Participants (N = 350) were trained to operate a complex computer-based simulation. Exploratory learning and error-encouragement framing had a positive effect on adaptive transfer performance and interacted with cognitive ability and dispositional goal orientation to influence trainees’ metacognition and state goal orientation. Trainees who received the emotion-control strategy had lower levels of state anxiety. Implications for developing an integrated theory of active learning, learner-centered design, and research extensions are discussed

Scaffolding online peer collaboration to enhance ill-structured problem solving with computer-based cognitive support.

The results reveal significant effects of procedure and metacognitive question prompts in ill-structured problem solving at both overall and univariate levels. However, there was no significant effect of online peer collaboration and no significant interaction. This study supported some previous research on using question prompts as a scaffolding strategy to support problem solving. Further, these findings support a redefined IDEAL problem solving model for solving ill-structured problems. The findings suggest many implications for instructional designers, educators in web-based learning environments, and educational researchers. These implications and the limitations of this study are discussed.The present study investigated the effects of question prompts and online peer collaborations on solving ill-structured problems. Sixty undergraduate students were randomly assigned to one of the four treatment groups: collaboration with question prompts, individual with question prompts, collaboration without question prompts, and individual without question prompts. Question prompts were designed to both facilitate problem solving procedure and promote students' metacognition. Students worked either individually or collaboratively with partners via MSN Messenger during the problem solving processes

Supporting Self-Regulated Learning in Online Learning Environments and MOOCs

Massive Open Online Courses (MOOCs) allow learning to take place anytime and anywhere with little external monitoring by teachers. Characteristically, highly diverse groups of learners enrolled in MOOCs are required to make decisions related to their own learnin

Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review

Massive Open Online Courses (MOOCs) allow learning to take place anytime and anywhere with little external monitoring by teachers. Characteristically, highly diverse groups of learners enrolled in MOOCs are required to make decisions related to their own learning activities to achieve academic success. Therefore, it is considered important to support self-regulated learning (SRL) strategies and adapt to relevant human factors (e.g., gender, cognitive abilities, prior knowledge). SRL supports have been widely investigated in traditional classroom settings, but little is known about how SRL can be supported in MOOCs. Very few experimental studies have been conducted in MOOCs at present. To fill this gap, this paper presents a systematic review of studies on approaches to support SRL in multiple types of online learning environments and how they address human factors. The 35 studies reviewed show that human factors play an important role in the efficacy of SRL supports. Future studies can use learning analytics to understand learners at a fine-grained level to provide support that best fits individual learners. The objective of the paper is twofold: (a) to inform researchers, designers and teachers about the state of the art of SRL support in online learning environments and MOOCs; (b) to provide suggestions for adaptive self-regulated learning support.Teaching and Teacher Learning (ICLON

Prompting Deliberation about Nanotechnology: Information, Instruction, and Discussion Effects on Individual Engagement and Knowledge

Deliberative (and educational) theories typically predict knowledge gains will be enhanced by information structure and discussion. In two studies, we experimentally manipulated key features of deliberative public engagement (information, instructions, and discussion) and measured impacts on cognitive-affective engagement and knowledge about nanotechnology. We also examined the direct and moderating impacts of individual differences in need for cognition and gender. Findings indicated little impact of information (organized by topic or by pro-con relevance). Instructions (prompts to think critically) decreased engagement in Study 1, and increased it in Study 2, but did not impact postknowledge. Group discussion had strong positive benefits for self-reported cognitive-affective engagement across studies. Also, for some types of engagement, effects were more positive for women than men. When predicting knowledge, there also was some evidence that discussion was more positive for women than men. Finally, need for cognition positively predicted engagement and knowledge gains, but rarely moderated the experimental effects. Given these mixed results, future research should continue to test theoretical assumptions about the effects of specific deliberative design features

Toward a Theory of Learner-Centered Training Design: An Integrative Framework of Active Learning

[Excerpt] The goal of this chapter, therefore, is to develop an integrative conceptual framework of active learning, and we do this by focusing on three primary issues. First, we define the active learning approach and contrast it to more traditional, passive instructional approaches. We argue that the active learning approach can be distinguished from not only more passive approaches to instruction but also other forms of experiential learning based on its use of formal training components to systematically influence trainees\u27 cognitive, motivational, and emotion self-regulatory processes. Second, we examine how specific training components can be used to influence each of these process domains. Through a review of prior research, we extract core training components that cut across different active learning interventions, map these components onto specific process domains, and consider the role of individual differences in shaping the effects of these components (aptitude-treatment interactions [ATIs]). A final issue examined in this chapter concerns the outcomes associated with the active learning approach. Despite its considerable versatility, the active learning approach is not the most efficient or effective means of responding to all training needs. Thus, we discuss the impact of the active learning approach on different types of learning outcomes in order to identify the situations under which it is likely to demonstrate the greatest utility. We conclude the chapter by highlighting research and practical implications of our integrated framework, and we outline an agenda for future research on active learning

Individual Learning In Team Training: Self-Regulation And Team Context Effects

Although many analysts recognize that team-level learning is reliant on the acquisition of learning content by individuals, very little research has examined individual-level learning during team training. In a sample of 70 teams (N = 380) that participated in a simulation-based team training setting designed to teach strategic decision-making, we examined how self-regulation during team training influenced the extent to which team members subsequently demonstrated individual mastery of the team training content. We also investigated the extent to which team characteristics moderated the relationships between self-regulation and learning outcomes. Multilevel mediation results indicated that self-efficacy fully mediated the effects of metacognition, or self-monitoring of learning, on individual declarative and procedural knowledge of team training content. The results also revealed that these individual-level relationships were moderated by the team context. In particular, a team’s overall performance and quality of cooperation amplified the positive effects of individual self-regulation. Implications for team training research and practice are discussed

Exploring the Hows and the Whos: The Effects of Self-Regulation Prompting and Goal Orientation on the e-Learning Process

This study investigated the effects that self-regulation prompts and goal orientation may exhibit on self-regulatory processes and subsequent learning. Specifically, a moderated mediation model was developed to explain how self-regulation prompts interact with prove performance goal orientation to affect two mediational processes, time on task and self-regulatory activity, and ultimately impact learning within a learner-controlled e-learning environment. To assess these hypotheses, an online Microsoft Excel instructional program was developed wherein 197 participants had control over when and where they completed training, the content they reviewed, the delivery medium (text-based or video-based), and the sequencing and pace at which they progressed through training. Participants in the experimental condition were periodically asked questions (i.e., self-regulation prompts) designed to encourage self-assessment of learning progress and strategies. All participants completed questionnaires before and after training. Findings did not support the hypothesized model. Implications and limitations as well as recommendations for future research will be discussed