Measuring Self-Regulated Learning Processes through Tracking Patterns of Student Interaction with Achievement Activities

A micro-level approach to the study of relationships between component processes within self-regulated learning in young adolescent students is described. Using this approach, contingencies between self-regulatory processes can be identified and insight into factors that promote students’ use of self-regulatory strategies can be investigated. Evidence is presented showing how the influence of mastery achievement goals on specific task goals can be mediated by students’ state of interest. Further development of this approach requires consideration of the measurement issues associated with using single items to measure on-task states. Evidence for the reliability and validity of single-item measurement of states is considered in relation to areas of psychological inquiry that regularly use single-item measures and we conclude that further development of these types of measure has the potential to expand our understanding of self-regulated learning.     

What changes,and for whom? A study of the impact of learning analytics-based process feedback in a large course

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.     

Comparing active delay and procrastination from a self-regulated learning perspective

Researchers have proposed that the act of postponing academic work may be divided into a traditional definition of procrastination, viewed as maladaptive, and adaptive forms of delay. Adaptive forms of delay may be more consistent with certain facets of self-regulated learning. The current study investigated this issue by examining whether the relations between aspects of self-regulated learning and active delay may be distinct from the relations these aspects of self-regulated learning have with procrastination. Among 206 undergraduates, procrastination was positively predicted by mastery-avoidance goals and negatively by metacognitive strategy usage, whereas active delay was negatively predicted by avoidance goals and positively by self-efficacy. Furthermore, students who reported higher levels of active delay also received better grades. These findings provide support that active delay is a distinct form of delay from procrastination that may be more positive due to its associations with some adaptive self-regulatory processes and academic achievement.     

Metacognition, achievement goals, study strategies and academic achievement: pathways to achievement

The purpose of this research was to develop and test a model of effective self-regulated learning. Based on effort expenditure we discerned effective self-regulators and less effective self-regulators. The model comprised achievement goals (mastery, performance-approach and -avoidance goals), metacognition (metacognitive knowledge, regulation and experience), study strategies (metacognitive, deep cognitive, surface cognitive and resource management strategies) and academic achievement. The relationships in the model were tested with controlling for intellectual ability, gender and age. The results showed that effective self-regulated learning involved two pathways: a metacognitive and a strategy pathway. The first pathway involved a positive relationship of mastery goals and a negative relationship of performance-avoidance goals with metacognition. Metacognition positively affected the use of the four study strategies. The strategy pathway involved positive effects of mastery and performance-approach goals on the use of metacognitive and deep cognitive strategies. Further, performance-approach goals positively affected the use of surface cognitive and resource management strategies. The use of metacognitive and resource management strategies had a positive and the use of surface cognitive strategies had a negative effect on exam scores.     

自我调节学习循环模式的实践应用

自我调节学习理论的提出主要来自于对美国三次教育改革运动的反思,相关研究以社会认知学派的影响最为广泛。进入20世纪80年代后,人们逐渐意识到智力和环境并不能完全解释学生学业成就的差异,学习者本人在学习活动中的作用越来越引起人们的关注。自我调节学习循环教学模式不仅凸显了学生的主体地位,还可以培养学生对学习策略的使用,教师在对学生使用自我调节学习循环模式进行指导时,也能够通过学生的反馈发现教学中的问题,从而加以改进,使得教学内容更符合学生的需求。     

浅谈电子闻览室对远程教育学生自主学习的支持和服务

电子阅览室为远程教育学生的独立探索提供了必要的学习资源环境和条件,已成为现代远程教育的支持体系。电子阅览室的管理人员不但要注重自身思想素质和业务技能的提高,还需要了解和熟悉远程教育,才能为远程教育学生自主学习提供优质的服务。     

How can primary school students learn self-regulated learning strategies most effectively?: A meta-analysis on self-regulation training programmes

Recently, research has increasingly focused on fostering self-regulated learning amongst young children. To consider this trend, this article presents the results of a differentiated meta-analysis of 48 treatment comparisons resulting from 30 articles on enhancing self-regulated learning amongst primary school students. Based on recent models of self-regulated learning, which consider motivational, as well as cognitive, and metacognitive aspects [Boekaerts, M. (1999). Self-regulated learning: Where we are today. International Journal of Educational research, 31(6), 445-457], the effects of self-regulated learning on academic achievement, on cognitive and metacognitive strategy application, as well as on motivation were analyzed. As the results show, self-regulated learning training programmes proved to be effective, even at primary school level. Subsequent analysis tested for the effects of several moderator variables, which consisted of study features and training characteristics. Regarding factors that concern the content of the treatment, the impact of the theoretical background that underlies the intervention was tested, as well as the type of cognitive, metacognitive, or motivational strategy which were instructed, and if group work was used as instruction method. Training context related factors, which were included in the analyses consisted of students’ grade level, the length of the training, if teachers or researchers directed the intervention, as well as the school subject in which context the training took place. Following the results of these analyses, a list with the most effective training characteristics was provided.     

现代远程教育环境下自主学习模式的构建

现代远程教育环境下自主学习模式的构建必须以建构主义的学习理论、现代远程教育学习理论和终生教育理论为基础；按照促进人的发展，继承与发展，有效获取信息，过程控制与反馈和动态权变的原则；从转换师生的角色，完善的自主学习支持服务体系，创设自主学习环境和建立科学的自主学习控制机制等方面入手。     

What can moment-by-moment learning curves tell about students’ self-regulated learning?

Many students in primary education learn arithmetic using adaptive learning technologies (ALTs) on tablets every day. Driven by developments in the emerging field of learning analytics, these technologies adjust problems based on learners' performance. Yet, until now it is largely unclear how students regulate their learning with ALTs. Hence, we explored how learners regulate their effort, accuracy and learning with an ALT using moment-by-moment learning curves. The results indicated that moment-by-moment learning curves did reflect students’ accuracy and learning, but no associations with effort were found. Immediate drops were associated with high prior knowledge and suboptimal learning. Immediate peaks were associated with robust learning and pointed to effective student regulation. Close multiple spikes showed moderate learning and lower initial levels of accuracy but, with system support, these students seemed able to regulate their learning. Separated multiple spikes indicated reduced learning and accuracy and potentially signal the inability of students to regulate their learning. In this light, moment-by-moment learning curves seem to be valuable indicators of accuracy regulation during learning with ALTs and could potentially be used in interventions to support SRL with personalized visualizations.     

The influence of achievement goal orientation on plagiarism

This investigation considered how undergraduate students with different achievement goal orientation profiles view plagiarism. Thai student volunteers (N = 867) completed an achievement goal survey [Niemivirta, M. (1998). Individual differences in motivational and cognitive factors affecting self-regulated learning — A pattern-oriented approach. In P. Nenninger, R. S. Jäger, A. Frey, & M. Woznitza (Eds.), Advances in motivation (pp. 23–42). Landau, DE: Verlad Empirische Pädagogik] and a “Dimensions of Plagiarism” survey [Koul, R. (2007). Dimensions of Plagiarism. Downloaded April 8, 2008 from http://dimensions-of-plagiarism.wikispaces.com/]. Mixed analysis of variance of attitudes towards plagiarism with goal orientation and gender showed several significant findings: high performance oriented students were substantially stricter than low performance orientated students in evaluating all Dimensions of Plagiarism. Low mastery oriented students were stricter regarding the “motive” dimension of plagiarism while high mastery oriented students were stricter regarding the “source” dimension of plagiarism. Significant differences between females and males were observed across the six factors of the Dimensions of Plagiarism survey. These results are interpreted within the framework of social comparison theory in respect to competitive learning environments.     

Learning from Learning Kits: gStudy Traces of Students’ Self-Regulated Engagements with Computerized Content

Researching self-regulated learning (SRL) as a process that evolves across multiple episodes of studying poses large methodological challenges. While self-report data provide useful information about learners’ perceptions of learning, these data are not reliable indicators of studying tactics learners actually use while studying, especially when learners are young children. We argue that self-reports about SRL need to be augmented by fine-grained traces that are records of learners’ actual activities as they study. We describe how gStudy software unobtrusively collects detailed trace data about learners’ use of study tactics as they engage with content presented in learning kits—collections of documents (e.g., texts, graphics, video clips) and tasks (e.g., notes, concept maps) on which learners operate to study. We suggest that trace data can advance research about how learners select, monitor, assemble, rehearse, and translate information to learn it, and provide raw materials for mapping SRL and its effects. Examples from the Life Cycles Learning Kit that supports grade 1 students learning about the life cycles of humans and frogs are given.