Facilitating Self-Regulated Learning with Technology: Evidence for Student Motivation and Exam Improvement

Barber, Larissa K.; Bagsby, Patricia G.; Grawitch, Matthew J.; Buerck, John P.

doi:10.1037/e566842012-648

Cited by 9 publications

(10 citation statements)

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“…As already stated, studies on learning quality improvements are closely related with feedback research (Barber et al, 2011;Butler & Winne, 1995). While feedback is usually given after a modeling task has been completed, referred to as outcome feedback, indicating whether or not results are correct (Butler & Winne, 1995), in the feedback research the effectiveness of more informative types of feedback that guide the process of cognitive activities is highlighted (Butler & Winne, 1995;Narciss, 2008;Shute, 2008).…”

Section: Related Workmentioning

confidence: 97%

“…Studies on learning quality improvements indicate a self-regulative approach as major source of impact on learning outcomes which in turn is closely intertwined with feedback research (Nicol & Macfarlane-Dick, 2006;Zimmerman, 2008), i.e. for all selfregulative activities, external feedback is considered as an inherent catalyst (Barber, Bagsby, Grawitch, & Buerck, 2011;Butler & Winne, 1995). As proposed by the constructivist approach (Hadjerrouit, 2005) the method of dialogue is the most optimal way to address learning difficulties by delivering personalized http://dx.doi.org/10.1016/j.chb.2014.09.054 0747-5632/Ó 2014 Elsevier Ltd. All rights reserved.…”

Section: Introductionmentioning

confidence: 99%

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Process mining analysis of conceptual modeling behavior of novices – empirical study using JMermaid modeling and experimental logging environment

Sedrakyan

Snoeck

Weerdt

2014

Computers in Human Behavior

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a b s t r a c tPrevious studies on learning challenges in the field of modeling focus on cognitive perspectives, such as model understanding, modeling language knowledge and perceptual properties of graphical notation by novice business analysts as major sources affecting model quality. In the educational context outcome feedback is usually applied to improve learning achievements. However, not many research publications have been written observing the characteristics of a modeling process itself that can be associated with better/worse learning outcomes, nor have any empirically validated results been reported on the observations of modeling activities in the educational context. This paper attempts to cover this gap for conceptual modeling. We analyze modeling behavior (conceptual modeling event data of 20 cases, 10.000 events in total) using experimental logging functionality of the JMermaid modeling tool and process mining techniques. The outcomes of the work include modeling patterns that are indicative for worse/better learning performance. The results contribute to (1) improving teaching guidance for conceptual modeling targeted at process-oriented feedback, (2) providing recommendations on the type of data that can be useful in observing a modeling behavior from the perspective of learning outcomes. In addition, the study provides first insights for learning analytics research in the domain of conceptual modeling.

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Section: Related Workmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Process mining analysis of conceptual modeling behavior of novices – empirical study using JMermaid modeling and experimental logging environment

Sedrakyan

Snoeck

Weerdt

2014

Computers in Human Behavior

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“…Yang, 2006). Barber, Bagsby, Grawitch, and Buerck (2011) examined the role of technology in facilitating self-regulated learning.…”

Section: The Role Of Student Variablesmentioning

confidence: 99%

MOOC-based flipped learning in higher education: students’ participation, experience and learning performance

Wang

Zhu

2019

Int J Educ Technol High Educ

107

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Relying on advanced network technologies, Massive Open Online Courses (MOOCs) can support the transformation and deep construction of high-quality open courses. However, with the use of MOOCs in many universities and colleges, new issues have emerged. MOOCs are not specifically designed for local conditions. Researchers lack understanding of the effectiveness of using shared MOOCs in traditional university teaching. The purpose of this study was to analyze the effectiveness of MOOC-based flipped learning and to propose clear reuse guidelines for MOOCs in the traditional university education. We conducted a quasi-experiment in an inorganic chemistry course. The results were presented in terms of learners' participation and learning performance, and a post-task survey and interviews were also conducted to investigate the students' experiences in order to include these experiences in design and research plans of MOOCs-based flipped learning. The results showed that students in the MOOC-based flipped classroom on average performed better than those in the traditional classroom. However, no changes in self-efficacy and selfregulated learning were detected after the end of the course. In addition, the quantitative and qualitative data combined indicated that most students had a favorable experience of the flipped classroom, in terms of student-student interaction, available learning materials, and active learning results. Implications for MOOC integration are discussed.

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“…Studies on learning quality improvements indicate a self-regulative approach as major source of impact on learning outcomes which in turn is closely intertwined with feedback research [16,17]. Furthermore, for all self-regulative activities, external feedback is considered as an inherent catalyst [18]. Usually this feedback is not available during learning activities but is given after a task has been completed.…”

Section: Requirements For Optimal Prototyping Environmentmentioning

confidence: 99%

Feedback-Enabled MDA-Prototyping Effects on Modeling Knowledge

Sedrakyan

Snoeck

2013

Enterprise, Business-Process and Information Systems Modeling

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This paper describes the effects of a feedback-enabled MDA prototyping tool on the validation cycle for conceptual models. We observe the effects of such prototyping method on learning outcomes of novice modelers. The impact is assessed based on the quality dimensions introduced by Conceptual Modeling Quality Framework (CMQF), more specifically with respect to semantic quality being affected by modeling knowledge. The current work proposes an extension to the techniques introduced in previous work in particular experimenting with the prototyping tool by novice modelers. A positive impact has been observed on the learning achievements of novice modelers improving both modeling and language knowledge.

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Facilitating Self-Regulated Learning with Technology: Evidence for Student Motivation and Exam Improvement

Cited by 9 publications

References 0 publications

Process mining analysis of conceptual modeling behavior of novices – empirical study using JMermaid modeling and experimental logging environment

Process mining analysis of conceptual modeling behavior of novices – empirical study using JMermaid modeling and experimental logging environment

MOOC-based flipped learning in higher education: students’ participation, experience and learning performance

Feedback-Enabled MDA-Prototyping Effects on Modeling Knowledge

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