Self-regulated learners are metacognitive, motivational, and behaviorally active participating in their own learning process (Zimmerman and Schunk, 2001, cited in Liaw and Huang, 2013). Self-regulated learning can be defined as the ability of a learner to actively monitor and control his or her own learning processes, such as setting learning goals, controlling the products produced, managing the effort involved, interpretatiing external feedback, creating strategies to reach the goals, providing self-feedback, etc., while maintaining a high level of motivation ( Nicol and MacFarlane-Dick, 2006 Zimmerman and Schunk, 1989). Pérez Garcias, in Formative Assessment, Learning Data Analytics and Gamification, 2016 2.1 Self-Regulated Learning Read moreĬollaborative e-Assessment as a Strategy for Scaffolding Self-Regulated Learning in Higher Education Low expectancies and values with respect to the future school career increase the probability of dropping out. Both expectancies and values are based on family background, school and class variables, and previous individual achievement-related experiences. Their study suggests that students who perceive their parents, teachers, and school administrations as supportive develop a higher level of perceived competence and academic autonomy, and that this leads to higher intrinsic academic motivation and a lower likelihood of leaving school without graduating.Įxpectancy-value models (e.g., Wigfield and Eccles 2000) suggest that academic choices are based mainly on expectancies of success in the domain of choice, and on how students value the domain. ( 1997) proposed a model assuming self-determined academic motivation to be an important factor influencing behavioral intentions and dropout behavior. In one of the few psychological studies on reasons for dropout, Vallerand et al. Schools, parents, and teachers provide an academic environment, and students' perceptions of this environment determine their achievement motivation, their behavioral intentions, and their academic behavior and choices. Köller, in International Encyclopedia of the Social & Behavioral Sciences, 2001 2.3 Individual Determinants of High School DropoutĪlthough many background and school variables are important antecedents of dropout, a more psychological view of the problem suggests that the concrete decision of whether or not to carry on or leave school is guided by individual characteristics such as attitudes and motivational states. At the core is the fear of giving up individual human rights of choice within one’s personal life. Looking through the philosophical lens of phenomenology, the researchers made meaning of the social media reflections and arrived at the essence of students’ emotional experiences. ![]() But what are student perceptions of using Facebook in formal learning, and what emotions and meaning arise as students think through such an experience? We asked 60 students to share their perceptions through a reflective process concerning the use of Facebook as a learning tool in coursework. Most research studies describe Facebook incorporation in the higher education classrooms where it has been used as a learning management system or a discussion board. The use of Facebook as a formal classroom tool continues to increase as educators innovate and experiment with its implementation. Pam Ponners, in Emotions, Technology, and Social Media, 2016 Abstract Read moreĪffective Impacts of Learning on Facebook The mentioned learning needs are used as the foundation for the learning design definition. Further, based on the students’ and teachers’ perceptions, other topics are lacking, such as the use of collaborative learning the students miss the social elements of traditional education ( Caño de Las Heras et al., 2020) and/or wish for a more dynamic and iterative simulator for open-ended exploration/investigation. ![]() Furthermore, ( Caño De Las Heras et al., 2021b) also reported that Python is the preferred language for modelling and optimization subjects. The study by ( Caño De Las Heras et al., 2021b, 2021c) has revealed that, according to the students' opinion, the programming content in the curriculum is not sufficient to cover the industry's future needs. Previous studies by the authors ( Caño De Las Heras et al., 2021b, 2021c), as well as others ( Balamuralithara & Woods, 2009 Dyrberg et al., 2017 Feisel & Rosa, 2005), have collected and quantified the students' perception on building on essential skills (e.g., programming) and on the use of simulators in their education. ![]() Ulrich Krühne, in Computer Aided Chemical Engineering, 2022 2.1 Identification of Learning requirements 14th International Symposium on Process Systems EngineeringĬarina L.
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