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Learning strategies and self-regulated learning
... Learners can sign up for a variety of MOOCs offered at no or a reasonably low cost, study at their own pace, and earn educational credentials from globally recognized universities. Since external support from instructors or peers are usually limited in MOOCs, the ability to self-regulate learning (SRL), that is, select and enact goal-oriented learning tactics that advance learning (Winne & Hadwin, 1998;Winne & Marzouk, 2019), comes to be a critical set of skills to successfully complete coursework (Kizilcec et al., 2017;Virtanen et al., 2017). Productive engagement in self-regulated learning, however, presents a challenge, in part because many learners struggle to enact effective learning tactics, that is, sequences of learning processes that a learner performs to master learning content and meet instructional expectations in a course (Azevedo et al., 2005;Bjork et al., 2013). ...
... Skilful self-regulated learners thus know which learning actions to invoke, how to compose a learning tactic from those actions and when to enact the tactic to advance their learning (Winne & Hadwin, 1998;Winne & Marzouk, 2019). Learning actions are specific learning events recorded in raw trace data , for example, a learner's click to play a video in MOOC is indicative of a 'Content_Access' action. ...
... For example, a learner may engage in the following learning actions to construct knowledge from course content: navigate a MOOC environment to find a page of interest, revisit a video lecture they watched earlier on that same page, and after that, read a relevant book chapter. It can be articulated from previous research (Azevedo et al., 2010;Bannert et al., 2014;Molenaar & Järvelä, 2014;Winne, 2010;Winne & Marzouk, 2019;Winne & Perry, 2000) that each learning action measured from trace data within different tactics can be described across four major dimensions (i) frequency, that is, how many times an action has been observed within a tactic in a given learning session; ...
Background
Select and enact appropriate learning tactics that advance learning has been considered a critical set of skills to successfully complete highly flexible online courses, such as Massive open online courses (MOOCs). However, limited by analytic methods that have been used in the past, such as frequency distribution, sequence mining and process mining, we lack a deep, complete and detailed understanding of the learning tactics used by MOOC learners.
Objectives
In the present study, we proposed four major dimensions to better interpret and understand learning tactics, which are frequency, continuity, sequentiality and role of learning actions within tactics. The aim of this study was to examine to what extent can a new analytic technique, the ordered network analysis (ONA), deepen the understanding of MOOC learning tactics compared to using other methods.
Methods
In particular, we performed a fine‐grained analysis of learning tactics detected from more than 4 million learning events in the behavioural trace data of 8788 learners who participated in a large‐scale MOOC ‘Flipped Classroom’.
Results and Conclusions
We detected eight learning tactics, and then chose one typical tactic as an example to demonstrate how the ONA technique revealed all four dimensions and provided deeper insights into this MOOC learning tactic. Most importantly, based on the comparison with different methods such as process mining, we found that the ONA method provided a unique opportunity and novel insight into the roles of different learning actions in tactics which was neglected in the past.
Takeaway
In summary, we conclude that ONA is a promising technique that can benefit the research on learning tactics, and ultimately benefit MOOC learners by strengthening the strategic support.
... Cognitive, motivational, emotional, and social elements all play a significant role in monitoring, regulating, and controlling one's learning in these theories (Pintrich et al. 2001). On the other hand, is defined by Winne as a metacognitive process aimed at adapting the usage of cognitive tactics and strategies to tasks (Winne 2015). Despite the disparities between models, there appears to be an accord that the self-regulated learning process involves several periods or stages. ...
... This behaviour change is represented in a sequence of actions or strategies in which the learner sets goals, monitors, regulates, and controls them, and is guided and controlled by those goals and the learning environment's contextual features (Pintrich 2000). In addition, the capacity of learners to choose and adapt their learning strategies according to the learning context is the key to engaging in self-regulated learning (Winne 2015). ...
p>The era of the coronavirus disease pandemic is increasingly driving the process of transforming teacher education and training from face-to-face to online-based. Besides having flexibility and accessibility, in practice, the transformation process has several weaknesses and challenges. One of them is a culture of self-regulated learning from the participating teachers. For this reason, the purpose of this article is to review self-regulated learning in online-based teacher education and training programs with key questions- how important is self-regulated learning in online-based teacher education and training programs? and how to facilitate the development of self-regulated learning in online-based teacher education and training programs? To answer this, we conducted a literature study of various books and previous research articles, so that the results were complete, both conceptually and empirically. As a result, self-regulated learning has become an important and strategic aspect for the success of any learner or online learning program, including online-based teacher education and training programs. For this reason, every designer, organizer and instructor need to facilitate the development of participants selfregulated learning aspects through their online learning platforms. Although it cannot be assumed that they will automatically and effectively develop their self-regulated learning skills, through deliberate design and facilitation efforts, they need to create and sustain the development of self-regulated learning skills of e-learners through rich learning experiences. Positive self-regulated learning tends to encourage the success of the online-based teacher education and training programs because teachers will give their best efforts to complete their online learning and have the potential to achieve the best results.</p
... The COPES model consists of five facets that take place in four linked phases. Changes in one phase would influence other phases during the whole learning process, while phases may not unfold in serial order as presented during learning process (Malmberg et al., 2017;Winne, 2015). This indicates that we should understand the SRL behaviors of learners in a dynamic way. ...
... Second, classifying the leaners according to SRL patterns helps to provide targeted intervention. Winne (2015) demonstrated that interventions that promoted SRL strategies can improve academic achievements. Nevertheless, not all students may benefit from SRL strategies, as students at different levels differed in learning strategy use or SRL abilities (Kim et al., 2018;Shih et al., 2010a). ...
To better understand the self-regulated learning process in online learning environments, this research applied a data mining method, the two-layer hidden Markov model (TL-HMM), to explore the patterns of learning activities. We analyzed 25,818 entries of behavior log data from an intelligent tutoring system. Results indicated that students with different learning outcomes demonstrated distinct learning patterns. Students who failed a problem set exhibited more passive learning behaviors and could hardly learn from practice, while students who mastered a problem set could effectively regulate their learning. Furthermore, we extended the use of TL-HMM to predicting learning outcome from behavior sequences and checked through cross-validation. TL-HMM is demonstrated helpful to gain insight into learners’ interactions with online learning environments. In practice, TL-HMM could be embedded in intelligent tutoring systems to monitor learning behaviors and learner status, so as to detect the difficulties of learners and facilitate learning.
... Previous work has shown that one of the common ways in which learners become careless and disengaged, is precisely gaming the system (Azevedo, 2015). Because learners intentionally decide how to regulate their engagement in (or disengagement from) learning, gaming the system, as procrastination and other self-handicapping techniques, is a form of SRL (Winne, 2015). In other words, SRL is not always beneficial and we should be talking of particular forms of SRL that lead to better learning, rather than SRL in general. ...
... Accordingly, it might be important to embed SRL support in the VEE, for example, through prompts (Hadwin, Wozney, & Pontin, 2005). The use of a questionnaire in this study has its limitations (Winne, 2015). It is known that students are not always accurate when reporting their own use of strategies (Boekaerts & Corno, 2005), and that questionnaires are static tools (Greene & Azevedo, 2010). ...
Virtual Experiment Environments (VEEs) have been shown as effective preparation steps for laboratory classes in natural science education. Given the self-directed nature of VEEs, students need adequate Self-Regulated Learning (SRL) skills. This study explores the relation between students' perceived SRL level and their behavior and outcomes in a VEE in the field of enzymology. Ninety-seven higher education students were divided into three groups of perceived SRL level (high, medium, and low). The VEE learning behavior (e.g., number of attempts and hints accessed) and VEE outcomes of these groups were compared while keeping prior knowledge as a covariate. While low self-regulated learners showed the least level of engagement with the VEE, high self-regulated learners showed the most optimum learning activity. Medium self-regulated learners engaged more in gaming the system behavior, and consequently learned the least. These results suggest that there is a nonlinear relationship between perceived SRL level and outcomes, since the intermediate level seems to be detrimental to learning, as explained through behavior. The intermediate level was characterized by an increase in agency, but a lack of goal-directed and planning behavior. Implications for self-regulated learning theory and the design of VEEs in the best interest of students are discussed.
... Entendemos el monitoreo metacognitivo como el seguimiento que el estudiante realiza durante el aprendizaje. Es una acción de toma de conciencia realizada por el estudiante sobre sí mismo y sobre sus propios recursos cognitivos al aprender, que implica el desarrollo de un estado de alerta con su propio conocimiento y capacidad para regular de manera intencionada y consciente su aprendizaje Montoya, 2021;Winne y Azevedo, 2014;Winne y Marzouk, 2019). Entre las cualidades de un buen monitoreo metacognitivo se han descrito: detectar errores, identificar las demandas de la tarea, precisar las estrategias de aprendizaje a seguir, optimizar procesos posteriores de aprendizaje, así como lograr mayor confianza y precisión de los juicios metacognitivos (Wang y Sperling, 2021;Winne y Azevedo, 2014). ...
Comprender el papel de los juicios metacognitivos en la enseñanza de las ciencias puede aportar de manera importante a cualificar los procesos educativos. Presentamos algunas de las relaciones existentes entre dos categorías teóricas importantes en la educación: los juicios metacognitivos y la Enseñanza de la Química desde la perspectiva de los niveles de representación. La investigación se realizó con profesores en formación de un programa de licenciatura en Ciencias Naturales de una universidad pública colombiana, a través de un diseño de investigación cualitativo concretado en un estudio de caso único. Los principales resultados indican la necesidad de insistir en la formación de maestros en el campo de metacognitivo y su influencia en la cualificación en los procesos de Enseñanza de la Química.
... En consecuencia, la AA se concibe como un fenómeno en el que los individuos sistemáticamente activan y sostienen un proceso cognitivo, motivacional/afectivo y conductual para lograr conocimientos, habilidades y destrezas, de manera eficaz en un determinado contexto (Azevedo, 2007;Schunk & Zimmerman, 1994;Winne, 2015;Zimmerman, 2008). Sin embargo, con la finali- ...
Las Actitudes hacia la asignatura Estadística Básica y la Autorregulación del Aprendizaje son factores fundamentales dentro del contexto educativo porque contribuyen al desarrollo de los procesos de planificación, ejecución y evaluación. La investigación tiene como propósito analizar la relación existente entre las variables, objeto de estudio por medio de las Escalas de Actitudes hacia la Estadística (AHE) e Inventario de procesos de autorregulación del aprendizaje (IPAA). El estudio es de carácter cuantitativo, descriptivo, de corte transversal, comparativo por género y correlacional. La muestra seleccionada fue de 570 estudiantes cuyas edades oscilan entre los 17 a 56 años. Los resultados reflejan que hay mayor correlación entre la Utilidad y la Confianza con el componente Ejecución. Además, se presentan diferencias por género (p> ,05) en el componente Utilidad, mientras que en los demás son similares. Se concluye que las actitudes hacia la estadística se relacionan de manera significativa con la Autorregulación del Aprendizaje, contribuyendo a la generación de competencias tales como la comunicación, el razonamiento y la resolución de problemas.
... Similarly, student learning strategies play a vital role in the effectiveness of online learning. Active learning strategies, such as learning by doing and group discussions, positively impact student satisfaction, while self-regulated learning strategies, including goal setting, time management, task strategies, and seeking help, act as effective safeguards for successful online learning (Garcia et al., 2018;Winne & Marzouk, 2019). However, since 2017, the frequency of this topic has shown a rapid decline, with a stagnant state observed after 2018, indicating a gradually weakening research frontier. ...
In the past, unfair business practices resulted in consumers suffering a host of abuses. Poverty, unequal
distribution of income and high litigation costs presented a challenge for consumers seeking justice. The
Consumer Protection Act 68 of 2008 (CPA) was enacted to protect consumers and prohibit unfair
business practices. It also placed restrictions on promotional methods. The overall aim of this paper is to
evaluate, through the findings from an empirical study, how consumer protection legislation in South
Africa impacts on promotional strategies of retail businesses. Using a qualitative methodology, the study
evaluated the implications of the CPA for retail businesses in South Africa. It firstly, explored specific
aspects pertaining to which provisions of the CPA affect the promotional efforts of retail businesses
(small to medium) in Durban; and secondly, it determined the implications of the implementation of the
CPA on promotional strategies of small to medium retail businesses in the Durban area. Eighteen
structured interviews were conducted with marketing managers and business owners. The findings from
the study identified several provisions of the CPA that have an impact on the way promotions are being
conducted currently. The study also showed that preferences for promotional tools are based on cost and
on reaching larger target audiences quickly, and that more expensive and labour-intensive measures were
adopted to address the restrictions of the CPA.
... Self-regulated learning is a learning process that is personally managed by each individual (Winne, 2015). This process involves self-direction of students in transforming mental abilities into certain academic skills that require motivation and consistency of thoughts, actions, and emotions so that the desired goals can be achieved (Zimmerman & Schunk, 2015). ...
span lang="EN-US">Students who cannot manage their learning independently other than in class will have an impact on their learning in class. Problems related to student self-regulated learning can be seen in the presence of students who forget to deliver assignments and students who have never reviewed the economics subject matter that has been taught. Based on preliminary observations, it is known that in MAN 3 Pekanbaru City there is no learning media that can support students to carry out self-regulated learning. Learning media that is only guided by textbooks is currently one of the learning methods that are not very effective for increasing self-regulated learning. This study aims to produce a valid and practical website-based learning media in economics subject at MAN 3 Pekanbaru so that it can effectively improve students' self-regulated learning. The development of website-based learning media is carried out using a 4-D model, namely define, design, develop, and disseminate. Data analysis was carried out descriptively and tested the effectiveness using paired sample t-test. The results of this study found that (1) the development of website-based learning media on material needs and scarcity was carried out using the 4-D model, namely (a) the defining stage (define) by conducting preliminary analysis, student analysis, task analysis, concept analysis, and analysis learning objectives; (b) the design stage by making flowcharts and storyboards and product design; (c) the development stage by validating two material experts and two media experts, then conducting a limited trial of 30 students and a wide-scale test on 36 class X students at MAN 3 Pekanbaru; (2) The validation rate of Website-based learning media in economics subjects at MAN 3 Pekanbaru is around 80% - 85%, which means that website-based learning media is very feasible and has very high validity; (3) the level of practicality of developing web-based learning media in economics subjects at MAN 3 Pekanbaru, namely teacher responses: very practical (88.67%), and student responses: very practical (87.90%); (4) the application of website-based learning media in economics subjects at MAN 3 Pekanbaru is effective in increasing student self-regulated learning</span
... As these models emerged from different theoretical backgrounds, they differ from each other. However, close analysis of these models suggests that despite the differences they share, major components of self-regulated learning described earlier and the difference between them lies in relative weightage assigned to these components (Puustinen & Pulkkinen, 2001;Winne, 2015). Overall, self-regulated learners are characterized as proactive learners who understand their strengths and learning needs. ...
Purpose: The motivated strategies for learning questionnaire (MSLQ) are extensively used by researchers and educators to measure self-regulated learning skills. The survey originally published in English has also been translated into multiple languages. However, a gap in the literature is found for its reliability and validity studies in the Pakistani context, specifically in the higher education sector. Therefore, this study was designed to establish the local norms and appraise the scale factors in specific samples and cultures. Methodology: Path analysis was used to examine the latent factor structures to determine whether MSLQ is appropriately reliable and valid to be used on our normative sample. All 15 subscales of the MSLQ were administered to a sample of 272 (n: 272) students enrolled in the undergraduate program of a private university located in Karachi, Pakistan. Findings: Results from the administration of MSLQ on a sample from the local population suggest that the scale is reliable and valid. Subscales (the exogenous variables) were loaded onto their respective factors with high regression weights. Statistically significant correlations were found among eleven subscales and the academic performances of students. The gender difference was found in eight subscales with significant Cohen's D. However, the model fit indices on SEM show a relative fit and poor fit on some of the indices. Conclusion: This study concludes that students' learning strategies and motivation have an impact on academic outcomes and considerable gender difference prevails in terms of motivation and learning strategies in Pakistani students.
... Based on the assessment system, in completing advanced statistics lecture assignments, students must have good self-regulation. Winne and Marzouk (2019) and Jansen, et al. (2019) stated that self-regulation itself is a description of students' ability to monitor, control, and direct aspects of their cognitive and affective processes in each learning process. Self-regulation includes several cognitive aspects, including: planning, monitoring, evaluating, and reinforcing (reinforming). ...
This study investigates the use of self-regulated in blended learning by students in doctoral education courses to complete advanced statistics lectures. Self-regulated in blended learning is described in four phases according to Zimmerman, namely planning, monitoring, evaluation, and reinforcing. The participants consisted of five students from 5 different disciplines, and were willing to share their learning experiences. Research data obtained by interview method and analyzed qualitatively. Validation uses two strategies, namely member checking and peer debriefing. Member checking is done after the data is formulated into themes, then the researcher will bring it back to the participants to find out their accuracy. Peer debriefing was conducted by colleagues to review and ask critical questions about this research. Colleagues have at least a doctoral degree. The results show that planning for the completion of student assignments begins with (1) setting goals and planning strategies with (a) planning time for completing assignments; (b) Cooperation with peers online and off-line; and (c) planning for technical issues; (2) Regularly calculate their scores every week after being given feedback on the results of the lecturer's assessment, and save the feedback results from completed assignments; (3) using assignment assessment rubrics, using lecturer feedback, and grades, to measure progress in lectures; (4) the strategies they have designed and implemented have succeeded in making success in doing the task.
... Self-regulated learning is based on knowing and applying learning strategies and an important ability for carefully handling personal resources (Winne 2015). Accordingly, learning strategies in general are activity sequences to reach learning goals and self-regulated learning refers to decisions learners make during their learning process. ...
To identify necessary content for teacher education, we first have to model professional competences of teachers as their abilities for applying a body of knowledge and concepts of physics to create an optimal learning environment. In general, competence can be seen as a cluster of characteristics including knowledge, skills, beliefs and abilities, which enable and improve the performance of a job. Consequently, competences always refer to a context and a task or problem to solve. Professional competence of physics teachers includes many areas of physics knowledge but also social and educational knowledge and skills to apply successfully to their teaching in the classroom. In the case of teaching physics, teachers’ professional competence requires their content knowledge on an adequate level but also their abilities, motivation and volition to teach physics in their respective classes. Beliefs and values of teachers often have their sources in everyday life as well as in the related scientific communities at university. Therefore, teachers should know the actual scientifically acquired knowledge about attitudes and values in order to identify their own attitudes and values and to assess their impact on teaching and learning. In addition, self-regulation competencies are necessary for teachers to organize their own working and their learning processes for keeping the development of their own resources.
... Cognitive & Metacognitively oriented (Flavell, 1976(Flavell, , 1979 Trace methodology • Metacognitive monitoring is the driver. (Winne, 2015;Winne & Perry, 2000). It can be measured as an aptitude, as a process, and through 'in the moment' measures' (Al' Adawi, 2021). ...
Evans, C., with Rutherford, S., Vieira, F., and Erasmus+ team (2021). A self-regulatory approach to assessment. Cardiff: Cardiff University.
This resource was developed to support implementation of self-regulatory approaches to assessment. It is underpinned by the Equity, Agency, Transparency (EAT) conceptual assessment framework which promotes an integrated and inclusive approach to assessment and feedback. The report aims to:
• Provide an overview of what self-regulation comprises.
• Highlight the conditions required to promote self-regulated learning (SRL).
• Identify what high level self-regulatory skills are.
• Provide a coordinating framework to support SRL development within assessment and feedback: Self-Regulatory Skills in Assessment Framework to support implementation of self-regulatory approaches in practice.
• Provide case study summaries of relevant SRL research in practice.
... Self-regulated learners are proactive learners who are aware of their strengths and weaknesses since they set goals for themselves and choose appropriate strategies (Zimmerman, 2002). Thus, those learners have also been defined as autonomous ones to control their learning and find reasonable solutions when needed (Winne, 2015). Therefore, understanding metacognition is strongly related to self-regulation of abilities (Schunk, 2001;Saraff et al., 2010). ...
... Self-regulated learners are proactive learners who are aware of their strengths and weaknesses since they set goals for themselves and choose appropriate strategies (Zimmerman, 2002). Thus, those learners have also been defined as autonomous ones to control their learning and find reasonable solutions when needed (Winne, 2015). Therefore, understanding metacognition is strongly related to self-regulation of abilities (Schunk, 2001;Saraff et al., 2010). ...
By Covid-19 pandemic online or distance learning came to foreground to resolve the educational crisis. Student-centred practices were recommended by educators to weather the storm. That’s why including self-regulated learning (SRL) and metacognitive learning strategies (MLS) to the online learning are considered necessary. Thus, this study aimed at investigating the use of self-regulated online learning (SROL) and MLS levels of students, the relationship between them, how the use of MLS predicts Turkish prospective teachers’ online SRL capacity through the time of emergency remote education, and contributing to the new educational paradigm after the pandemic. The study was designed as a correlational survey model including 567 prospective teachers at Fırat University Faculty of Education in Turkey. The data were collected by MLS determining scale and SROL questionnaire for prospective teachers. The data were analyzed by t-test, ANOVA and simple linear regression. The results revealed that the participants have high levels of SROL and use MLS frequently. While SROL and MLS levels of participants do not differ in terms of gender; they differ with regard to participants’ departments, class levels and time of self-study. Lastly the use of MLS was a positive predictor of SROL.
... Das Lernen wird dabei als systematischer und kontrollierbarer Prozess, der maßgeblich in der Verantwortung des Lernenden steht, betrachtet (vgl. Winne, 2015;Zimmerman, 1990). Zur Beschreibung selbstregulierter Lernprozesse haben sich, in Anlehnung an Regelkreismodelle der Kybernetik, eine Reihe zyklischer Phasenmodelle etabliert (Landmann, Perels, Otto & Schmitz, 2009;Schmitz & Wiese, 2006;Zimmerman & Moylan, 2009). ...
... La investigación sugiere que las intervenciones educativas aumentan la precisión del monitoreo y mejoran el aprendizaje (Gutierrez & Schraw, 2015;Gutierrez de Blume, 2017;Huff & Nietfeld, 2009;Thiede, Griffin, Wiley & Redford, 2009). Estas intervenciones son importantes porque la capacitación de estrategias cognitivas produce un conjunto duradero de habilidades de autorregulación que pueden ser utilizadas en una variedad de entornos por parte de alumnos de secundaria o universitarios que de otra manera podrían experimentar una variedad de dificultades de aprendizaje (Greene & Azevedo, 2010;Winne & Marzouk, 2019;Winne & Nesbit , 2009). Sin embargo, la mayoría de estos estudios han implementado diseños cuasiexperimentales, en lugar de experimentos puros (cf. ...
Antecedentes: El monitoreo, como componente de regulación de la metacognición, es un aspecto esencial del aprendizaje autorregulado. El monitoreo se reconoce como la capacidad del alumno para comprender con éxito lo que está aprendiendo y, por lo general, implica actividades metacognitivas como preguntas, reflexiones, inferencias y retroalimentación autogenerada. Sin embargo, pocos estudios hasta la fecha han examinado la influencia de la capacitación en estrategias cognitivas para la precisión del monitoreo metacognitivo de los alumnos. Objetivo: La presente investigación exploró el efecto del capacitación en estrategias cognitivas para la precisión del monitoreo metacognitivo de los alumnos universitarios de Estados Unidos (N = 62) después de la intervención, mientras que se controlaba estadísticamente la precisión del monitoreo previo a la intervención, para ello, se empleó un diseño de investigación experimental. Metodología: Los alumnos fueron asignados al azar al grupo de entrenamiento de estrategias (n = 31) o al grupo de control (n = 31). Resultados: Los resultados revelaron que los alumnos expuestos a capacitación de estrategias cognitivas demostraron un monitoreo significativamente más preciso que los alumnos que formaron parte del grupo control, incluso después de ajustar la precisión del monitoreo antes de implementar la intervención. Conclusiones: Los profesores de aula pueden emplear la capacitación de estrategias cognitivas específicas en su práctica diaria para mejorar los resultados del aprendizaje entre sus alumnos, y esta capacitación se puede realizar de forma sucinta, obviando así la necesidad de demasiado tiempo adicional.
... by Winne[18]), such as obtaining the homework credit for each module. On theFIG. ...
In two earlier studies, we developed a new method to measure students’ ability to transfer physics problem-solving skills to new contexts using a sequence of online learning modules, and implemented two interventions in the form of additional learning modules designed to improve transfer ability. The current paper introduces a new data analysis scheme that could improve the accuracy of the measurement by accounting for possible differences in students’ goal orientation and behavior, as well as revealing the possible mechanism by which one of the two interventions improves transfer ability. Based on a 2×2 framework of self-regulated learning, students with a performance-avoidance oriented goal are more likely to guess on some of the assessment attempts in order to save time, resulting in an underestimation of the student populations’ transfer ability. The current analysis shows that about half of the students had frequent brief initial assessment attempts, and significantly lower correct rates on certain modules, which we think is likely to have originated at least in part from students adopting a performance-avoidance strategy. We then divided the remaining population, for which we can be certain that few students adopted a performance-avoidance strategy, based on whether they interacted with one of the intervention modules designed to develop basic problem-solving skills, or passed that module on their first attempt without interacting with the instructional material. By comparing to propensity score matched populations from a previous semester, we found that the improvement in subsequent transfer performance observed in a previous study mainly came from the latter population, suggesting that the intervention served as an effective reminder for students to activate existing skills, but fell short of developing those skills among those who have yet to master it.
... Classical conceptual approaches to metacognition are understood as the capacity that allows students to know themselves and consciously inspect their own cognition and its attributes such as how they think and with what information they think, then charting and then mentally following a path of action to achieve a learning goal (Winne & Marzouk, 2019). In this sense, Schraw (2002) has argued that cognition and metacognition differ in that cognitive skills are necessary to perform a task while metacognition is necessary to understand how the task was executed (Garner, 1987;Schraw, 2002). ...
Metacognitive skills such as when and why to apply strategies successfully given task demands (conditional knowledge) and those that assist in regulation like comprehension monitoring are essential for effective learning. However, the debate regarding whether metacognitive skills are domain general or domain specific continues to rage among scholars. Presumably, if metacognitive skills are domain specific, there should be significant differences between domains whereas if they are domain general, there should be no differences across domains. Thus, in the present study we examined the generality/specificity of metacognitive skills (knowledge of cognition: declarative, procedural, and conditional; regulation of cognition: planning, information management, debugging, comprehension monitoring, and evaluation) in a sample of Colombian university students (N = 507) studying education (n = 156), psychology (n = 166), and medicine (n = 185) employing the Spanish version of the Metacognitive Awareness Inventory. Results revealed that there were significant differences in all but two metacognitive skills (procedural knowledge and debugging) across domains, largely supporting the domain specific hypothesis, but also partially supporting the domain general view. Implications and recommendation of the findings for theory, research, and practice are discussed.
... In addition, we examine two potential side effects of using extra credit incentives to reduce cramming and procrastination. First, research on student self-regulated learning (SRL) suggests that some learners may focus more on achieving extrinsic goals, in this case acquiring the extra credit [19][20][21]. For those learners, it is possible that they will replace one cramming session with multiple cramming sessions to earn the extra credit without increasing their study time on learning materials. ...
... SRLs also have a relatively high level of selfefficacy and motivation, which function as catalysts for goal setting and strategy use (Bandura, 2015). SRLs are strategic, autonomous and proactive learners who can control their learning and try to overcome the difficulties in the learning process (Goulão & Menedez, 2015;Pintrich et al., 1991;Winne, 2015), which eventually increases the possibility of a high level of academic achievement. ...
Article History: Purpose: This research aims to examine self-regulated learning (SRL) skills of undergraduate students (USs) and reveal the role of higher education programs in promoting SRL skills. Research Methods: In this mixed-method research, the participants consisted of 1411 freshmen and senior students and 17 senior-year interviewees. Data collection tools included Personal Information Form, Self-Regulatory Learning Scale and semi-structured interview form. Findings: The findings obtained in this study showed that SRL skills of USs were moderate. SRL skills of USs significantly differed in accordance with gender, grade level, foreign language preparatory education, the high school type students graduated from and the motive for choosing the program. The qualitative findings of the study revealed that a wide range of elements regarding curriculum, instruction, instructors and other components of higher education programs were substantially significant in enhancing SRL. Implications for Research and Practice: As a result of this research, it can be suggested that higher education programs in the sample do not adequately promote SRL skills of undergraduate students. The inclusion of SRL-promoting-elements in the curriculum and instructional processes are bound to the instructors who design their own courses. Considering most of the faculty members have not received a comprehensive pedagogical and andragogical education, SRL might have a long way to get in to the agenda of tertiary instructors. Therefore, the tertiary instructors are highly suggested participating in a continuous and comprehensive pedagogical training focusing on the good teaching practices that can foster SRL and desirable learning outcomes.
... Decisions learners make about self-regulation either promote or impede their achievement. Evidence suggests that productive self-regulated learning can be fostered through evidenced-based designs for learning activities and environments, by promoting particular beliefs among teachers, and helping learners discover value in education [40]. Studies conducted in order to evaluate whether reflection journal writing was effective in promoting self-reflection and learning, and whether students become better at self-reflection if they are engaged in this type of activity suggest that self-reflection does lead to improvements in academic performance [41]. ...
This paper addresses the problem of the formation of the self-regulation of educational activities of students studying in a technical university. The purpose of this paper is to discuss the problem of the self-regulation of educational activities of students, presenting data from an experimental study of students’ self-regulation. Special attention is paid to the distinction between the terms self-control and self-regulation. This paper presents data on the state of self-regulation among students studying technical specialties. The research methodology is based on the theoretical analysis of the results of scientific works, which present the main provisions on the formation of students’ self-regulation. The research methods include questioning and a methodical experiment. The stages of the formation of students’ self-regulation are highlighted, and the main directions of teachers’ work on the formation of students’ self-regulation are determined. The structure of self-regulation is described and the condition for its formation is justified using the technology of self-regulation formation. Based on the study, students’ self-regulation is linked to the awareness of their professional and personal goals, as well as to the level of regulatory and reflective qualities. Personal and professional self-improvement in the process of vocational education depends on the level of the formation of regulatory and reflexive qualities.
Keywords Self-regulation; self-control; independent activity of students; professional culture; learning activities; self-regulation technology
... nStudy is currently being augmented with learning analytics designed to motivate and guide students towards productive self-regulated learning (Winne, 2017;Winne & Marzouk, 2019). Marzouk et al. (2016) described how learning analytics, beyond simply mirroring learners' behaviour, can visualise students' engagement with resources in ways that represent their learning strategies and foster their metacognition and motivation to learn. ...
The term cognitive tool has been used in many areas of academic specialisation, where it has taken on multiple connotations. In this historical and systematic review, we investigate the conceptualisation of cognitive tools in the learning sciences and educational technology. First, the theory of cognitive tools vis-à-vis learning and development is traced from Vygotsky and Soviet psychology through to its use in current educational technology and learning design. Second, we present a systematic review of cognitive tools in peer-reviewed research literature. We found the term cognitive tool was often used vaguely or with extreme generality. When used more specifically, it referred to communication methods such as visualisations, metaphors, symbols, and hypermedia; or interactive interfaces and environments such as templates, databases, simulations, games, and collaborative media. We offer a definition of software-based cognitive tools founded on the attributes of representation, interactivity, and distributed cognition, which commonly feature in the work of influential theorists; and we explain implications of the definition for designing, evaluating, and researching learning technologies.
... En general, la autorregulación de la conducta implica el establecimiento de metas, la evaluación de los objetivos, la reacción emocional al progreso o la falta de progreso y la gestión de recursos hacia la consecución de objetivos, o en su defecto, a la renuncia a los objetivos (Vanthournout et al., 2015;Forgas, Baumeister y Tice, 2009). En consecuencia, en esta teoría, el aprendizaje autorregulado se concibe como un fenómeno donde los individuos sistemáticamente activan y sostienen un proceso cognitivo, motivacional/afectivo y conductual para lograr conocimientos, habilidades y destrezas, de manera eficaz en un determinado contexto (Winne, 2015;Schunk y Zimmerman, 1994;Schunk, 2004;Azevedo, 2007;Zimmerman, 2008). ...
Este ensayo consiste en una revisión bibliográfica que expone los conceptos de aprendizaje autorregulado y de autorregulación del aprendizaje en el marco de la teoría sociocognitiva. Se hace necesario explicar dos elementos fundamentalmente relacionados: la autoeficacia y la motivación. Además, se explica el vínculo entre la autorregulación del aprendizaje y las competencias que diversos especialistas y organismos internacionales consideran importantes para la formación de los docentes. A lo largo de todo el ensayo se proponen líneas de investigaciones viables, válidas y pertinentes, referidas al aprendizaje autorregulado, algunos conceptos asociados y sus relaciones con otras variables de interés psicopedagógico, en estas propuestas se enfatiza la educación formal y la formación de docentes.
Understanding processes in self-regulated learning (SRL) and tailoring appropriate instructional support to help students become more productive self-regulated learners has been on the agenda of SRL researchers for decades. New data modalities and analytic methods are becoming increasingly available to augment existing methodologies, enhance SRL measurement, test theoretical assumptions about SRL and inform future instructional support. Though promising, this research direction is yet to be fully explored. To learn more about how multimodal learner data and analytic methods can be used to improve research and support for SRL, we invited for a conversation Professors Maria Bannert, Inge Molenaar, and Phil Winne, three prominent scholars who have been extensively researching SRL over the past few decades. The conversation included two parts (1) Studying SRL via Analytics and (2) Supporting SRL via Analytics. The discussion identified several major areas for future research, including integrating multiple data channels in a meaningful way to improve theoretical understanding of SRL, and supporting learners by offering them options on what to do next, rather than by saying that they missed an opportunity to engage in a particular SRL process. Following the polyphonic research methodology, the lead authors and the interviewed SRL scholars co-authored this chapter. A podcast of the conversation is available at https://spotifyanchor-web.app.link/e/NwvHdDh3MMb.
Generative artificial intelligence (GAI) has revolutionised the landscape of academic writing, presenting both advantages and risks to learning for L2 writers. It is thus imperative that L2 writers, especially at advanced academic levels, develop the critical skills necessary for employing GAI tools ethically and effectively in their writing processes. Our study addressed this need by 1) conceptualising Critical GAI Literacy based on current research and our collected data, and 2) developing a self-regulated learning-based micro-curriculum for L2 doctoral students to cultivate knowledge and skills using GAI for academic writing. We collected interactive and reflective data in an introductory-level academic writing course at a Swedish university enrolled with 60 PhD students from diverse backgrounds and examined their evolving perspectives and strategies for engaging in GAI-mediated writing. Findings show a spectrum of initial attitudes among students and limited knowledge of GAI use. Final reflections illustrate de-enchantment with GAI, recali-brated and enhanced understanding of ethical issues, developed prompting methods, and increased awareness of text ownership through the self-directed learning process. Furthermore, students demonstrated a discerning approach in evaluating GAI-generated suggestions and so-ciolinguistic impacts, indicating a growing criticality in L2 writing practices.
Massive Open Online Courses (MOOCs) are highly beneficial to the public. However, much research demonstrated low completion numbers of MOOC learners. Several factors have been identified as influential factors in the success of MOOC learners. However, a few studies examined the extent to which prior knowledge is associated with completion rates, learning outcomes, and patterns of student engagement. Hence, this paper aims to examine the relationships between prior knowledge, knowledge gains, and engagement patterns of MOOC learners. Specifically, this study used data mining techniques based on the patterns of learning performance. The Kruskal-Wallis test was used to examine the differences in terms of performance among the detected clusters. Process mining was then used to explore the learning process. The results demonstrated that five groups of learners were identified based on the patterns of their performance calculated from the score obtained from pre-tests (prior knowledge) and post-tests (learning gains) for each of the five topics, namely, Dropout, Stable, Progress, Late dropout, and Post attempt groups. Among the five groups, two of them exhibited different dropout behaviours, namely a) those who dropped out after scoring highly on the pre-test in the first topic in the MOOC and b) those who received relatively low scores in both pre-and post-tests on each topic they studied. This offers a novel insight into MOOC research while indicating that dropout may not be always associated with a lack of success. The study also demonstrated differences in the learning strategies that were
In this scientific investigation, the researchers have designed and developed a new model The Framework of Self-Regulated Cognitive Engagement (FSRCE) that integrates self-regulated learning (SRL) and cognitive engagement (CE), addressing the limitations of previously developed frameworks. The FSRCE model is guided by core principles, emphasizing the dynamic SRL loop, two dimensions of cognitive engagement, individual and contextual factors, ongoing adaptation, and the integration of cognitive and behavioral engagement. In the dynamic SRL loop, the model unfolds in four phases: the forethought phase, performance phase, monitoring and feedback loops, and self-reflection phase. These phases illustrate the iterative nature of SRL and emphasize the importance of CE at each stage. The cognitive engagement depth dimension measures the intensity of cognitive involvement, while the cognitive engagement strategies dimension examines the specific strategies students employ. Individual and contextual factors, including intrinsic motivation, goal orientation, self-efficacy beliefs, and external influences, significantly shape CE within the FSRCE framework. Students’ intrinsic motivation and goal orientation drive their engagement, while self-efficacy beliefs influence their ability to regulate their learning processes effectively. Continuous adaptation and optimization are central to the FSRCE model, allowing students to adjust their cognitive engagement in response to evolving task demands and feedback. It underscores the interplay between cognitive and behavioral engagement, recognizing that both dimensions are integral to achieving optimal learning outcomes, and provides students with a blueprint for active participation in their learning, optimizing their CE, and enhancing learning outcomes, thereby shedding light on the path to more effective and meaningful educational experiences.
Introduction
Self-regulated learning (SRL), or learners’ ability to monitor and change their own cognitive, affective, metacognitive, and motivational processes, encompasses several operations that should be deployed during learning including Searching, Monitoring, Assembling, Rehearsing, and Translating (SMART). Scaffolds are needed within GBLEs to both increase learning outcomes and promote the accurate and efficient use of SRL SMART operations. This study aims to examine how restricted agency (i.e., control over one’s actions) can be used to scaffold learners’ SMART operations as they learn about microbiology with Crystal Island, a game-based learning environment.
Methods
Undergraduate students (N = 94) were randomly assigned to one of two conditions: (1) Full Agency, where participants were able to make their own decisions about which actions they could take; and (2) Partial Agency, where participants were required to follow a pre-defined path that dictated the order in which buildings were visited, restricting one’s control. As participants played Crystal Island, participants’ multimodal data (i.e., log files, eye tracking) were collected to identify instances where participants deployed SMART operations.
Results
Results from this study support restricted agency as a successful scaffold of both learning outcomes and SRL SMART operations, where learners who were scaffolded demonstrated more efficient and accurate use of SMART operations.
Discussion
This study provides implications for future scaffolds to better support SRL SMART operations during learning and discussions for future directions for future studies scaffolding SRL during game-based learning.
Was passiert mit der Lesekompetenz, wenn die KI Texte produziert? Das Lesen hat mit der Zunahme von Lesesituationen mit Internetdokumenten bereits eine Ausdifferenzierung und Aufwertung evaluativer Fähigkeiten erfahren, die mit Textbots wie ChatGPT nochmals verstärkt wird. Die Herausforderung ist zunächst gleich: Das Internet offeriert Aussagen und Quellen variierenden Geltungsanspruchs in puncto Wahrheit bzw. Glaubwürdigkeit, und kompetente Leser:innen müssen durch die Konjunktur von ChatGPT & Co. – und das ist das Neue – mehr denn je damit rechnen, auf gut geschriebene Texte zu stossen, die sie sorgfältig zu prüfen imstande sein sollten. Evaluative Fähigkeiten wirken damit immer nötiger, der Beitrag systematisiert sie. // What happens to reading skills when AI produces texts? With the increase in reading situations involving internet documents, reading has already undergone a differentiation and reappraisal of evaluative skills - a development being further intensified by textbots such as ChatGPT. The challenge for readers is at first the same: the internet offers statements and sources with varying claims in terms of truth or credibility. However, with the rise of ChatGPT & Co. competent readers must expect more than ever to encounter well-written but epistemically insecure texts that they should be able to check carefully. Evaluative skills thus seem to become more and more crucial, the article systematizes them.
Recent advances in the use of learning technologies for both in-person and distance education has enabled the collection of detailed data on learners’ access and use of resources at unprecedented levels. Simultaneously, the growth of technology use in the classroom has brought forward increased interest in the analysis and use of learner data. The field of learning analytics leverages these data with the aim to enhance understanding about and improve learning processes. The Society of Learning Analytics Research defines learning analytics as “the measurement, collection, analysis and reporting of data about learners and their context” (LAK in 1st international conference on learning analytics and knowledge, Banff, AB, Canada, 2011; SOLAR in What is learning analytics? 2021). This chapter provides an overview of leveraging learning analytics to enhance understanding and provide feedback about learning processes. We aim to offer insights into types of data used to generate learning analytics, use the research on procrastination as an example for interpreting and operationalizing learning processes through data and analytics, and offer recommendations for generating feedback about these data. We aim to offer a starting point for utilizing learning analytics and convey their potential to aid learning and pedagogical choices.
Metacognition is thinking about the contents and processes of one’s own cognition. Research shows that metacognition plays important roles in most cognitive tasks, from everyday behaviors to problem-solving to expert performance. This chapter focuses on metacognition’s centrality in learning and in self-regulated learning. When learning, people monitor what they know and whether it is aligned with their intended learning outcome. A learner’s ability to monitor effectively is known as calibration. Learners then control their next actions based on their monitoring, and finally they self-regulate the process of monitoring and controlling their learning by shaping and adapting cognition or behavior by reaching forward by planning for future tasks. Research shows that people learn better when they have strong metacognitive abilities and when they can self-regulate their learning effectively.
The interdisciplinary field of the learning sciences encompasses educational psychology, cognitive science, computer science, and anthropology, among other disciplines. The Cambridge Handbook of the Learning Sciences, first published in 2006, is the definitive introduction to this innovative approach to teaching, learning, and educational technology. In this significantly revised third edition, leading scholars incorporate the latest research to provide seminal overviews of the field. This research is essential in developing effective innovations that enhance student learning - including how to write textbooks, design educational software, prepare effective teachers, and organize classrooms. The chapters illustrate the importance of creating productive learning environments both inside and outside school, including after school clubs, libraries, and museums. The Handbook has proven to be an essential resource for graduate students, researchers, consultants, software designers, and policy makers on a global scale.
Learning sciences are embracing the significant role technologies can play to better detect, diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with the measurement of SRL processes to advance our understanding of how multimodal data can unobtrusively capture learners' cognitive, metacognitive, affective, and motivational states over time, tasks, domains, and contexts. This paper introduces a self-regulated learning processes, multimodal data, and analysis (SMA) grid and maps joint and individual research of the authors (63 papers) over the last five years onto the grid. This shows how multimodal data streams were used to investigate SRL processes. The two-dimensional space on the SMA grid is helpful for visualizing the relations and possible combinations between the data streams and how the measurement of SRL processes. This overview serves as an analytical introduction to the current special issue “Advancing SRL Research with Artificial Intelligence (AI)” and we encourage to position new research and unexplored frontiers. We emphasize the need for intensive and strategic collaboration to accelerate progress using new interdisciplinary methods to develop accurate measurement of SRL in educational technologies.
This research study aimed to determine the effectiveness of Strategic Intervention in Guiding Learners' Aptitude (Project SIGLA) in improving the academic performance of Grade 12 students in Health Optimizing Physical Education (HOPE) 4 subject. Project "SIGLA" was one of the pedagogies and initiatives done for Grade 12 students at Buenaventura Alandy National High School (BANHS) in Tayabas City to bridge the gap in students' academic performance by developing self-paced modules that allow students to deal with the lesson and improve exam results even without in-depth discussions. Descriptive-comparative research method was used in gathering quantitative data from the Diagnostic Test (Pre-test), Achievement Test (Post-test) and survey questionnaire. The respondents were thirty (30) Grade 12 students from various strands of Buenaventura Alandy National High School (BANHS)'s Academic, Technical Vocational, and Livelihood Track. The findings of the study reveals that (1) the pre-test scores were low and that the respondents were not adapted to the "New Normal" learning modality, resulting in poor academic performance in the HOPE 4 subject, (2) the post-test scores increased after Project "SIGLA" was implemented, indicating that the intervention was successful owing to the developed self-made learning material, (3) the contents of the self-made learning material were appropriate for modular distance learning, activities suited the learning styles of the learners, instructions were clear and understandable, and that the assessments enable learners to answer objectively with comprehension and critical thinking, (4) significant difference on the respondents' pretest and post-test scores owed to implementation of the Project "SIGLA" which enhanced academic achievement in HOPE 4, and (5) weak connections were found between the respondents' knowledge of factual, conceptual, and analytical components and the self-developed module's content, activities, teaching, and evaluation at the α = 0.05 level. The results of this study contribute to the literature and body of knowledge concerning academic performances improvement through developed self-made learning material intervention.
In this chapter, we explore inclusive learning analytics to predict reading comprehension outcomes in the context of middle school remedial reading classrooms for 235 students from 12 school districts in the United States. The design of the system used in this study followed the Universal Design for Learning Guidelines which have expressed the goal of supporting all learners, a common goal with inclusive learning analytics. We construct a predictive model for reading comprehension, introducing a novel method to apply the same sentiment analysis method to interpret both emotional self-reports and discussion comments, contributing new insights about the relationship between emotion and cognition during learning. The novel method of analysis was inspired by the inclusive design principles of Universal Design for Learning by treating the two data sources as multiple means of expression. The relationship the model suggests is that struggling students with positive emotional reactions coupled with neutral communication about reading materials are more likely to provide correct answers. The psychological phenomena of positive internal experience coupled with downregulated expression have previously been described as “smiling on the inside,” and are considered socially desirable when outperforming peers. We explore the model in terms of bias across a range of groups legally protected from discrimination. With the limitations of the measures and the model in mind, we provide recommendations on how to support students in this psychological state of “smiling on the inside”.KeywordsInclusive learning analyticsUniversal design for learningReading comprehensionMiddle school
When writers mine information from multiple sources to develop an essay, they reinterpret and reorganize their knowledge as they pursue and, possibly, reshape goals for rhetorical structure. Such writing tasks are popular across age levels and domains. It is assumed cognitive processes engaged in this kind of task provide practice that improves writing skills and deepens engagement with content. However, writing grounded in multiple and typically diverse sources is a demanding task. Successfully synthesizing information across multiple sources calls on multiple and interwoven cognitive and metacognitive processes as authors balance work in rhetorical, content and metacognitive spaces. To successfully traverse this complex and evolving cognitive landscape shaped by multidimensional goals, writers need procedural knowledge that operationalizes skills plus broad conditional knowledge to guide using those skills. For these reasons, success in multi-source writing tasks requires extensive and productive self-regulation. To advance research on these issues and give direction to engineering writing analytics to support productive self-regulation in multi-source writing, we synthesized research accessing and synthesizing content across multiple sources (Cho et al., Strategic processing in accessing, comprehending, and using multiple sources online. In: Handbook of multiple source use. Routledge, pp 133–150, 2018; Perfetti et al., Toward a theory of documents representation. In: The construction of mental representations during reading. Psychology Press, p 88108, 1999; Rouet et al., Educ Psychol 52(3):200–215, 2017; Rouet and Britt, Relevance processes in multiple document comprehension. In: Text relevance and learning from text. Information Age Publishing, Inc., pp 19–52, 2011), writing processes (Bereiter and Scardamalia, The psychology of written composition. Hillsdale, 1987) and self-regulated learning (SRL; Winne, Cognition and metacognition within self-regulated learning. In: Schunk D, Greene J (eds) Handbook of self-regulation of learning and performance, 2nd edn. Routledge, pp 36–48, 2018; Winne and Hadwin, Studying as self-regulated learning. In: Hacker DJ, Dunlosky J, Graesser A (eds) Metacognition in educational theory and practice, Erlbaum, pp 277–304, 1998). The result is a two-dimensional typology of cognitive and metacognitive processes in self-regulated writing using multiple sources (SR-WMS) spanning two problem spaces in writing tasks, rhetorical and content.KeywordsSelf-regulationMulti-source writingMultiple source comprehensionnStudyLearning analytics
Metacognition is the engine of self-regulated learning. At the object level, learners seek information and choose learning tactics and strategies they forecast will develop knowledge. At the meta level, learners gather and analyze data about learning events to draw conclusions, such as: Is this tactic a good fit to conditions? Was it effective? Was effort required reasonable? Is my ability publicly exposed? As data accumulate, learners shape, re-shape and refine a personal theory about optimal learning. Thus, self-regulating learners are learning scientists. However, without training and tools on which “professional” learning scientists rely, learners’ N = me research programs are naïve and scruffy. Merging models of tasks, cognition, metacognition and motivation, I describe software tools, approaches to analyzing data and learning analytics designed to serve three goals: supporting self-regulating learners’ metacognition in N = me research, accelerating professional learning scientists’ research, and boosting synergy among learners and learning scientists to accelerate progress in learning science.
The increasing digitalization and automatization in the manufacturing industry as well as the need to learn on the job has reinforced the need for much more granular learning, which has not yet impacted the design of learning materials. In this regard, granular learning concepts require situated learning materials to support self-directed learning in the workplace in a targeted manner. Co-creation approaches offer promising opportunities to support employees in the independent design of such situated learning materials. Using an action-design research (ADR) approach, we derived requirements from co-creation concepts and practice by conducting focus group workshops in manufacturing and vocational training schools to develop design principles for a co-creation system that supports employees through the creation process of work-process-related learning material. Consequently, we formulate four design principles for the design of a collaborative learning and qualification system for manufacturing. Using an innovative mixed methods approach, we validate these design principles and design features to demonstrate the success of the developed artifact. The results provide insights regarding the design of a co-creation system to support learners in the co-creation of learning material with the consideration of cognitive load (CL). Our study contributes to research and practice by proposing novel design principles for supporting employees in peer creation processes. Furthermore, our study reveals how co-creation systems can support the collaborative development of learning materials in the work process.
Massive Open Online Courses (MOOCs) have already shown a great potential to be used as an alternative model for teacher professional development (TPD). Not only do MOOCs offer relevant content and activities, but they also provide opportunities for strengthening the skills for self-regulated learning of teachers as life-long learners. In this study, we focused on a unique sub-group of MOOC learners – retakers who take the same TPD MOOC multiple times. In the empirical study reported in this paper, we examined what learning strategies they choose when taking a TPD MOOC and the extent to which they are able to adapt their learning strategies to improve their performance in the subsequent attempts. By using learning analytic methods, we detected five learning strategies and eight major forms of strategy change adapted by MOOC retakers. We found that two strategy changes (from Content-Oriented Strategy to Intensive-Thorough Strategy or Balanced Strategy) with associated with significantly higher performance in the subsequent attempts compared to no change in strategy. Our findings have implications for MOOC instructors and providers about the ways they can support MOOC retakers. Our findings also suggest that MOOCs are not only valuable TPD resources for teachers, but they also have unique opportunities for strengthening the self-regulation skills of teacher learners as the “by-products of learning”.
There is a tendency to think of the impact of educational technology in a vacuum. However, it is likely that the instructional context in which educational technology is used affects student learning. For instance, outcomes may differ when using educational technology in a classroom versus at home, in a quiet versus noisy environment, or in a context where support is readily available versus not available. The COVID-19 pandemic provided an unexpected opportunity to explore this issue. Intending to explore how providing hints and feedback within a digital learning game (Game X) impacts mathematics learning, we instead found ourselves exploring a new question: How did learning with the game differ between classrooms and at home? After two of five middle schools had participated in our classroom experiment, we switched to at-home use of the Internet-based gamefor the final three schools due to the pandemic. The different instructional settings led to significantly different completion rates, likely due to students in the classroom (N = 151) being monitored by experimenters and teachers (completion rate of 88.8%), while students at home (N = 126) were not monitored nor strictly required to finish (completion rate of 56.5%). In addition, the two versions of the game, one that provided students with on-request hints and error feedback (Hint condition) and one that did not (No-Hint condition), led to different classroom versus at-home results. On the delayed posttest, students in the No-Hint condition did significantly better in the classroom, while there was no significant difference between conditions at home. In addition, students in the Hint condition used significantly more hints in the classroom than they did at home. There was also a significant effect of gender in the classroom, with female students out-performing male students on the immediate posttest, but with no effect of gender remotely. We performed post-hoc analyses to better understand students’ learning processes and gameplay behaviors. In summary, our study clearly illustrates how educational technology can be sensitive to instructional context, yet just cracks open the door to much more research on this topic.
Epistemisch wachsames Lesen aus theoretischer Sicht zu konturieren, bildet das Ziel des Beitrags. Er hat folgenden Aufbau: Zu Beginn steht der Blick in eine exemplarische aktuelle Studie aus den USA, welche zeigt, wie immens hoch der lesedidaktische Handlungsbedarf ist, Jugendliche zur kritischen Nutzung des Internets zu befähigen (1). Im darauffolgenden Hauptteil des Beitrags (2) werden das epistemisch wachsame Lesen definiert und vier zentrale kognitive Komponenten dargestellt. Ein Fazit schließt den Beitrag ab (3).
How do performing arts students negotiate their time and tasks while regulating, i.e. monitoring and controlling, their resources and prioritising tasks in becoming a performing artists?
Este estudio indaga sobre la autoeficacia para la escritura académica que un grupo de profesores de idiomas en formación en México tiene ante la escritura colaborativa de un artículo de investigación documental en inglés, mediada por WebQuest-Wiki. En particular se investiga: 1) los niveles de autoeficacia antes y después de la tarea; 2) las fuentes de la autoeficacia que los estudiantes traen a la tarea; 3) la autoeficacia emanada de las acciones y los medios en la tarea. El diseño mixto incluyó el uso del cuestionario “Percepción de la autoeficacia para la escritura académica en inglés”, la información de encuadre del curso y un cuestionario que evaluó WebQuest-Wiki. Un T-test (pre-post, sin grupo control) resultó significativo con p < 0,05 para los
factores “autoeficacia para el aprendizaje”, “conocimiento local y global del proceso de escritura” y “autorregulación metacognitiva”. En cambio, no se modificaron los factores “convenciones en la escritura”, “generación de ideas”, “tiempo/esfuerzo” y “respuesta física”. Las fuentes principales de la autoeficacia alta inicial observada en el uso de “convenciones en la escritura” y “autoeficacia para el aprendizaje” son las
prácticas previas de textos descriptivos y la confianza en obtener logros satisfactorios en su estudio. El proyecto WebQuest-Wiki incrementó la percepción de tener más control sobre la comprensión del contenido de los textos leídos y del uso de estrategias de comprensión de vocabulario, del uso de habilidades específicas de escritura académica para el tipo de texto específico y en ver a sus iguales como modelos de la actividad por realizar.
This paper reports the findings of a study that proposed a novel learning analytic methodology that combines process mining with cluster analysis to study time management in the context of blended and online learning. The study was conducted with first-year students (N = 241) who were enrolled in blended learning of a health science course. The study identified four distinct time management tactics and three strategies. The tactics and strategies were interpreted according to the established theoretical framework of self-regulated learning in terms of student decisions about what to study, how long to study, and how to study. The study also identified significant differences in academic performance among students who followed different time management strategies.
Blended forms of learning have become increasingly popular. However, it remains unclear under what circumstances blended learning environments are successful. Studies suggest that blended learning challenges learners’ self-regulation. Yet little is known about what self-regulatory behaviour learners exhibit in such environments. This limited understanding is problematic since this insight is needed for effective designs. Therefore, the aim of this study was to identify learners’ self-regulatory behaviour profiles in blended learning environments and to relate them to designs of blended learning environments. Learners’ (n = 120) self-regulatory behaviour in six ecologically valid blended learning courses was captured. Log files were analysed in a learning analytics fashion for frequency, diversity, and sequence of events. Three main user profiles were identified. The designs were described using a descriptive framework containing attributes that support self-regulation in blended learning environments. Results indicate fewer mis-regulators when more self-regulatory design features are integrated. These finding highlights the value of integrating features that support self-regulation in blended learning environments.
A bottleneck in gathering big data about learning is instrumentation designed to record data about processes students use to learn and information on which those processes operate. The software system nStudy fills this gap. nStudy is an extension to the Chrome web browser plus a server side database for logged trace data plus peripheral modules that analyze trace data and assemble web pages as learning analytics. Students can use nStudy anywhere they connect to the internet. Every event related to creating, modifying, reviewing, linking and organizing information artifacts is logged in fine grain with a time stamp. These data fully trace information students operate on and how they operate on it. Ambient big data about studying gathered au naturel can be tailored by configuring several of nStudy’s features. Thus the system can be used to gather data across a wide range lab studies and field trials designed to test a range of models and theories.
Information literacy (IL) is the set of skills and knowledge that allows us to find, evaluate, and use the information we need, as well as to filter out the information we don’t need. IL skills are the necessary tools that help us successfully navigate the present and future landscape of information. Information and technology affects every person in every possible setting—work, education, recreation. This paperoffers an overview of IL focusing on three contexts for successful IL learning and teaching: (i) the information process itself, (ii) technology in context, and (iii) implementation through real needs in real situations. The author covers conceptual understandings of IL, the range of IL standards and models, technology within the IL framework, and practical strategies for effective IL skills learning and instruction in a range of situations.http://dx.doi.org/10.14429/djlit.28.2.166
Six features are enumerated that distinguish studying from learning in general and describe circumstances that essentially compel students to engage in complex bundles of goal-directed cognitive and motivational processes that 'get studying done.' We view these bundles as instances of metacognitively powered self-regulated learning. As a first step toward examining studying through metacognitive lenses, we present a general typology that delineates facets of academic tasks in general, including studying tasks. Then, we use this typology to characterize four distinguishable but recursively linked stages of studying: task definition, goal setting and planning, enacting study tactics and strategies, and metacognitively adapting studying. Next, we develop connections between our typology for studying and models of metacognitive monitoring, metacognitive control, and self-regulated learning. With this backdrop, we then survey select research that highlights metacognitive activities in each of the four stages of studying. Finally, we summarize our model of studying and offer suggestions for next steps in research on studying as a complex, self-regulated learning event.
Learners working on major learning projects, such as an undergraduate thesis, frequently engage in information problem solving (IPS). In round-trip IPS, learners set goals and develop a work plan, search for and filter sources, critically analyze and mine key information, and draft and revise a final product. Information problem solving is a prime site for self-regulated learning (SRL) whereby learners formulate and carry out self-designed experiments to improve IPS skills and expand knowledge about the topic of the learning project. We describe nStudy, a software system developed to gather ambient trace data that operationally define features of IPS and SRL as learners work on learning projects. We illustrate how trace data can be used to promote learners’ (a) understanding of the topic of a learning project and (b) development of IPS by generating learning analytics, guidance in the form of quantitative and qualitative accounts describing information learners work with and operations they apply to information. Three main challenges are addressed: learning how to plan a learning project, expanding knowledge of the topic of a learning project, and benefiting from and productively contributing to peer reviews of draft products. We conjecture about an emerging ecology for IPS in which big data and learning analytics can be major resources for education.
Background
Today's gold standard for identifying what works, the randomized controlled trial, poorly serves each and any individual learner. Elements of my argument provide grounds for proposed remedies in cases where software can log extensive data about operations each learner applies to learn and each bit of information to which a learner applies those operations.
Purpose of Study
Analyses of such big data can produce learning analytics that provide raw material for self-regulating learners, for instructors to productively adapt instructional designs, and for learning scientists to advance learning science. I describe an example of such a software system, nStudy.
Research Design
I describe and analyze features of nStudy, including bookmarks, quotes, notes, and note artifacts that can be used to generate trace data.
Results
By using software like nStudy as they study, learners can partner with instructors and learning scientists in a symbiotic and progressive ecology of authentic experimentation.
Conclusion
I argue that software technologies like nStudy offer significant value in supporting learners and advancing learning science. A rationale and recommendations for this approach arise from my critique of pseudo-random controlled trials.
Interest in learning strategies and study tactics seems at all-time high. In this chapter, approaches to studying are conceptualized as self-regulated learning whereby learners survey tasks, generate goals and devise plans for studying, study and make on-the-spot adaptations, and may substantially renovate studying methods. Relative to this framework, the content of books describing learning strategies is examined, methods used to research learners’ approaches to studying are analyzed, and results of studies investigating the effects of learning strategies/study tactics are summarized. Shortcomings of research methodologies may account for overall modest and rather variable findings about the benefits of learning strategies/study tactics. Also, factors are identified that may hinder learners’ uptake and productive use of learning strategies/study tactics. A plan is proposed for improving and accelerating research on learning strategies. It involves learners as colleagues in personalized programs of research that, in the aggregate, advance learning science.
Research and development of instructional computing systems (ICSs) are exploring the frontiers of knowledge in both computing and instructional sciences. While these efforts are slowly advancing knowledge, they have not yet produced practical ICSs that can be readily used in educational settings. I propose a retreat to regions where knowledge is relatively more firmly established, regions I call “merely” state-of-the-art. Specifically, a state-of-the-art ICS would be built on knowledge of computing systems and instruction that is available now rather than on knowledge in the process of being found by research at the frontier. I propose developing a state-of-the-art ICS that teaches learners how to read so that their comprehension exceeds that gained by reading a superior textbook. I sketch a theory of instruction that underlies the instructional features of a state-of-the-art ICS focussed on this objective. Then, I illustrate in “paperware” form what this ICS might look like. I conclude by describing how work at the frontier of ICSs can be advanced by using a state-of-the-art ICS to bootstrap knowledge needed.
Only about a decade after initial projects emerged, learning analytics have already had a profound effect on how institutions view the combination and use of multiple data sets and their subsequent analysis on learners and instructors. The success or failure of these institutional projects lay in the confluence of the data that is available, the extent to which analysis is conducted on that data, and the ensuing action taken on the results. Some higher education institutions have begun using the power of analytics to affect positive outcomes in critical areas like learning, pedagogy, student retention, and institutional decision-making (Long and Siemens 2011). But what does analytics mean to an institution and how might an institution implement some form of analytics? Further, what can institutions expect from the successful implementation of analytics?
High quality learning is extensive, well integrated, deep, and supports the use of knowledge in new situations that require adaptation of what has been learned previously. This book reviews current research on the nature of high quality learning and the factors that facilitate or inhibit it. The book addresses relationships between quality of learning and learners' dispositions, teaching methods, cognitive strategies, assessment and technologies that can support learning. The chapters provide theoretical analyses, reports of classroom research, and suggestions for practical application for both teachers and learners. The book will be of value to teachers at all levels of education and provides guidance for students about how to approach classroom tasks in order to develop high quality learning.
Realizing the promise of software technologies in education requires thinking differently about how software simultaneously can serve research and contribute to learning. This article examines 3 axioms underlying contemporary educational psychology: Learners construct knowledge, learners are agents, and data include lots of randomness. By drawing out corollaries of these axioms, this research uncovers significant challenges researchers face in using classical forms of experimental research to build a basis for school reform and for testing school reforms using randomized field trials. This article describes a software system, gStudy, that is designed to address these challenges by gathering finer grained data that better support theorizing about the processes of learning and self-regulated learning. This research illustrates how this can be realized and suggests 10 ways that using software like gStudy can help pull up research by its bootstraps and bolster searches for what works.
Are preventive early childhood interventions effective in improving home environments, as assessed with the HOME inventory (Caldwell & Bradley, 1984)? The authors traced 48 published articles, presenting 56 intervention effects (N = 7,350). The combined effect size on the HOME total score was d = 0.20 (p < .001). Randomized intervention studies were effective, but the combined effect size was limited (d = 0.13). Nonrandomized studies showed inflated effects (d = 0.58). Interventions with middle-class, non-adolescent parents showed higher effect sizes than interventions with low-SES or adolescent samples. Effective interventions used a moderate number of sessions in a limited period and were home-based. Learning Materials, Involvement, and Responsivity showed significant intervention effects. Families in better living conditions profited more from parent education (the Matthew effect).
Prior research on learning from instruction has used a three-stage model of effects. The model posits that (1) an instructional stimulus cues the learner to use particular cognitive processes to operate on content, (2) these operations are executed, and (3) the result facilitates learning. While theories focus on all three stages, experiments have provided only indirect evidence about how well each is accomplished and rarely have controlled directly all three key sources of variance. An illustrative analysis of learning from instruction is presented, and a procedure is proposed that probabilistically increases control over the theoretically significant cognitive causes of instructional effects.
Electric cars pros and cons
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It takes more than a major: Employer priorities for college learning and student success
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