New Pedagogies of Motivation: Reconstructing and Repositioning Motivational Constructs in the Design of Learning Technologies

Magnifico, Alecia Marie; Olmanson, Justin; Cope, Bill

doi:10.2304/elea.2013.10.4.483

Cited by 10 publications

(4 citation statements)

References 47 publications

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“…This result reinforces the importance of giving students the role of protagonist in the learning process, even though using a ctional narrative. The mere fact of changing their status from student to intern, and from the classroom to a startup, seems to have produced nice results (Magni co et al, 2013).…”

Section: Resultsmentioning

confidence: 99%

Introductory Physics Laboratory as an opportunity to promote students´ soft skills

Zacharias

Monteiro

2022

Preprint

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Any professional should be competent in managing information to solve real and new problems. The concept of competence involves more than conceptual and procedural skills and takes into account socio-emotional issues. Experimental classes in Physics usually aim to develop technical skills. However, these can be an effective opportunity to promote soft skills. In this article, a gamified online class concerning introductory experimental physics is reported. Storytelling proved to be an important engagement drive, favoring meaningful and long-term learning. Students declared a high confidence level to reproduce experimental activities, despite having had no access to the laboratory facilities. They have highlighted critical thinking and logical reasoning, proactivity, ability to work under pressure, and time management as those most promoted skills. These results suggest that classes can be designed to deliver not only technical skills but also promote soft skills, transforming an Introductory Physics Laboratory into an opportunity to contribute to a better professional formation.

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Section: Resultsmentioning

confidence: 99%

Introductory Physics Laboratory as an opportunity to promote students´ soft skills

Zacharias

Monteiro

2022

Preprint

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“…They also transform them by using quite different kinds of evidentiary argument from those of the past. Foundational areas for big data and data science in education include: formative and situated or classroom assessment (Black & Wiliam, 1998;Pellegrino, Chudowsky, & Glaser, 2001); technology-mediated psychometrics (Chang, 2015;Rupp, Nugent, & Nelson, 2012); self-regulated learning and metacognition (Bielaczyc, Pirolli, & Brown, 1995;Bransford, Brown, & Cocking, 2000;Kay, 2001;Kay, Kleitman, & Azevedo, 2013;Lane, 2012;Magnifico, Olmanson, & Cope, 2013;Shepard, 2008;Winne & Baker, 2013); and analyses of complex performance and holistic disciplinary practice (Greeno, 1998;Mislevy, Steinberg, Breyer, Almond, & Johnson, 2002).…”

Section: Disciplinary Realignmentsmentioning

confidence: 99%

Interpreting Evidence-of-Learning: Educational research in the era of big data

Cope¹,

Kalantzis²

2015

Open Review of Educational Research

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In this article, we argue that big data can offer new opportunities and roles for educational researchers. In the traditional model of evidence-gathering and interpretation in education, researchers are independent observers, who pre-emptively create instruments of measurement, and insert these into the educational process in specialized times and places (a pre-test or posttest, a survey, an interview, a focus group). The 'big data' approach is to collect data through practice-integrated research. If a record is kept of everything that happens, then it is possible analyze what happened, ex post facto. Data collection is embedded. It is on-the-fly and everpresent. With the relevant analysis and presentation software, the data is readable in the form of data reports, analytics dashboards and visualizations. We explore the methodological consequences of these developments for research methods.

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“…Video games were massively popularized with the rise of personal computing in the 1980s, and today reach an audience larger than Hollywood. The question educators have been attempting to address is how can we bring the medium and levels of engagement of games to education through the 'gamification' of learning (Gee, 2005;Magnifico, Olmanson, & Cope, 2013)? James Gee identifies 36 learning principles that are intrinsic to most video games, even first person shooter games, many of which are absent or at best weakly present in what he characterizes as 'traditional schooling' (Gee, 2004).…”

Section: Learning Gamesmentioning

confidence: 99%

“…Motivation and affect are key factors in learning (Magnifico et al, 2013). Log files can provide indirect evidence of patterns of engagement, or more specific information such as the extent to which a learner relies on help offered within the environment (Rebolledo-Mendez, Boulay, Luckin, & Benitez-Guerrero, 2013).…”

Section: Affect Metersmentioning

confidence: 99%

Sources of Evidence-of-Learning: Learning and assessment in the era of big data

Cope¹,

Kalantzis²

2015

Open Review of Educational Research

Self Cite

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This article sets out to explore a shift in the sources of evidence-of-learning in the era of networked computing. One of the key features of recent developments has been popularly characterized as 'big data'. We begin by examining, in general terms, the frame of reference of contemporary debates on machine intelligence and the role of machines in supporting and extending human intelligence. We go on to explore three kinds of application of computers to the task of providing evidence-of-learning to students and teachers: (1) the mechanization of tests-for instance, computer adaptive testing, and automated essay grading; (2) data mining of unstructured data-for instance, the texts of student interaction with digital artifacts, textual interactions with each other, and body sensors;(3) the design and analysis of mechanisms for the collection and analysis of structured data embedded within the learning process-for instance, in learning management systems, intelligent tutors, and simulations. A consequence of each and all of these developments is the potential to record and analyze the 'big data' that is generated. The article presents both an optimistic view of what may be possible as these technologies and pedagogies evolve, while offering cautionary warnings about associated dangers.

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New Pedagogies of Motivation: Reconstructing and Repositioning Motivational Constructs in the Design of Learning Technologies

Cited by 10 publications

References 47 publications

Introductory Physics Laboratory as an opportunity to promote students´ soft skills

Introductory Physics Laboratory as an opportunity to promote students´ soft skills

Interpreting Evidence-of-Learning: Educational research in the era of big data

Sources of Evidence-of-Learning: Learning and assessment in the era of big data

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