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Self-regulated learning (SRL) is critical for learning across tasks, domains, and contexts. Despite its importance, research shows that not all learners are equally skilled at accurately and dynamically monitoring and regulating their self-regulatory processes. Therefore, learning technologies, such as intelligent tutoring systems (ITSs), have been designed to measure and foster SRL. This paper presents an overview of over 10 years of research on SRL with MetaTutor, a hypermedia-based ITS designed to scaffold college students' SRL while they learn about the human circulatory system. MetaTutor's architecture and instructional features are designed based on models of SRL, empirical evidence on human and computerized tutoring principles of multimedia learning, Artificial Intelligence (AI) in educational systems for metacognition and SRL, and research on SRL from our team and that of other researchers. We present MetaTutor followed by a synthesis of key research findings on the effectiveness of various versions of the system (e.g., adaptive scaffolding vs. no scaffolding of self-regulatory behavior) on learning outcomes. First, we focus on findings from self-reports, learning outcomes, and multimodal data (e.g., log files, eye tracking, facial expressions of emotion, screen recordings) and their contributions to our understanding of SRL with an ITS. Second, we elaborate on the role of embedded pedagogical agents (PAs) as external regulators designed to scaffold learners' cognitive and metacognitive SRL strategy use. Third, we highlight and elaborate on the contributions of multimodal data in measuring and understanding the role of cognitive, affective, metacognitive, and motivational (CAMM) processes. Additionally, we unpack some of the challenges these data pose for designing real-time instructional interventions that scaffold SRL. Fourth, we present existing theoretical, methodological, and analytical challenges and briefly discuss lessons learned and open challenges., Competing Interests: EC was employed by the Soar Technology, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Azevedo, Bouchet, Duffy, Harley, Taub, Trevors, Cloude, Dever, Wiedbusch, Wortha and Cerezo.)

The implementation of the European higher education area (EHEA) is a true paradigm change in university education in which the student, with particular consideration given to autonomous work, takes the place of the teacher as the central element of the teaching-learning process. In this autonomous work, the strategies the students regularly use become particularly important, given the supposition that doing that work will lead to academic success. The objective of this study is to analyze the variables that influence students' expectations of success, measured through their intention to persist on the course they are doing. A questionnaire designed ad hoc was given to a sample of 1037 university students. It included aspects related to reasons for choosing the course, institutional integration, use of self-regulation strategies, and intention to drop out. Data analysis allowed the identification of satisfaction with the course chosen and appropriate study skills acquired in secondary education as predictors of expectations of academic persistance, with some differences in terms of gender. Other strategies such as class attendance or going deeply into course content did not figure. These results are at odds with the principles underlying the EHEA and show that they have not yet been interiorized by the students, who continue to perceive their studies more traditionally., (Copyright © 2019 Bernardo, Esteban, Cervero, Cerezo and Herrero.)

Adolescence is an especially risky phase for the appearance of antisocial behaviors. Antisocial behavior produces significant individual and social harms, so it is important to provide keys for prevention and treatment. To do that, it is essential to identify the main predictors. The objective of this study is to analyze the effect of family (affection and communication, behavioral control) and friends (antisocial friendships) on adolescent antisocial behavior, as well as the mediating role of adolescent impulsivity and empathy on these relationships. Previously validated questionnaires measuring parental affection and communication, and behavioral control, as well as adolescent impulsivity, empathy, antisocial friendships, and antisocial behavior were applied to 3199 adolescents in Asturias (Spain), aged between 11 and 18 (M = 14.03; SD = 1.39). Descriptive, correlational, and structural equation analysis were performed. Antisocial friendships were a risk factor for antisocial behavior in adolescence, with a moderate effect size. The effect is mostly direct, although it is also indirect through the positive relationship with adolescent impulsivity and low empathy. The two analyzed parenting style dimensions (affection and communication, and behavioral control) demonstrate a protective effect, albeit small, on adolescent antisocial behavior. There is a direct protective effect, but it is mostly indirect through the negative relationship with antisocial friendships and low adolescent empathy. Parental behavioral control can be a risk factor for antisocial behavior, through the positive relationship with adolescent impulsivity. This study helps to clarify the causal mechanisms of antisocial behavior in adolescence, as a basis for its prevention and treatment.

The aim of this work is to analyze the relationship between parental control and cyber-victimization in adolescence, considering the possible mediating effect of impulsivity, and high-risk internet behavior. To that end we analyzed the responses of 3360 adolescents aged between 11 and 18 ( M = 14.02; SD = 1.40), from Asturias (Spain), to four previously validated questionnaires in order to measure the level of parental control over the use of the internet (restriction and supervision), along with high-risk internet behaviors, impulsivity, and cyber-victimization in the adolescents. The results show that parental control tends to have a protective effect on the likelihood of the children being victims of cyber-aggression, with impulsivity, and high-risk internet behaviors as mediating variables. More specifically, parental restriction and supervision are positively related to each other; both forms of parental control are negatively related with the adolescent's engaging in high-risk internet behaviors; supervision is negatively related with impulsivity; impulsivity is positively related with high-risk internet behaviors; and both impulsivity and high-risk internet behaviors are positively related to being a victim of cyber-aggression. The practical implications of these results are discussed.

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs) . Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.