Active teaching to manage course difficulty and learning motivation

Andres, Hayward P.

doi:10.1080/0309877x.2017.1357073

Cited by 33 publications

(33 citation statements)

References 47 publications

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“…As for the third question (Q3), we expect, based on previous findings (Barba et al, 2016;Burns et al, 2020;Hidi, 1990;Niemivirta & Tapola, 2007;Nuutila et al, 2020;Richardson et al, 2012;Rotgans & Schmidt, 2018;Schöber et al, 2018;Talsma et al, 2018;Vainikainen et al, 2015), the initial levels of situational interest and self-efficacy to be predictive of task performance. Similarly, in line with both direct and indirect evidence (Andres, 2019;Guthrie et al, 2009;Power et al, 2020;Steensel et al, 2019), we presume the level of perceived difficulty to have a negative effect on performance, beyond and above the effects of self-efficacy and interest. The potential effects of changes in each construct on performance remain more speculative.…”

Section: Present Studysupporting

confidence: 80%

“…properties of the task, and peripheral cues, such as perceptions of one s performance, feelings of fatigue, and completion time (Koriat, 1997;Vangsness & Young, 2017, 2019. In a sense, then, feelings of difficulty during a task can be seen as metacognitive experiences that play an important role in a person s self-regulation and online awareness as the tasks unfold (Efklides, 2001).…”

Section: Judgements Of Difficulty Depend On Central Cues Such As Objmentioning

confidence: 99%

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Mutual relationships between the levels and changes in interest, self-efficacy, and perceived difficulty during a task

Nuutila¹,

Tapola²,

Tuominen³

et al. 2021

Preprint

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This study examined how students’ interest, self-efficacy, and perceived difficulty change during a task, how those changes relate to each other, and how they predict performance. Sixth-graders (N = 1024) rated their interest, self-efficacy, and perceived difficulty repeatedly during a dynamic problem-solving task. Results from the estimated non-linear and piecewise latent growth curve models showed interest and self-efficacy to decrease, and perceived difficulty first to increase, and then to decrease, over time. The levels of and changes in interest and self-efficacy correlated positively with each other, but negatively with perceived difficulty. Task performance was positively predicted by initial interest and less negative change in self-efficacy, and negatively by initial perceived difficulty and steeper increase in it. The results suggest perceived difficulty to have a distinctive role in the dynamics of task-specific motivation, and on-task changes to be relatively independent of more general motivation and competence.

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Section: Present Studysupporting

confidence: 80%

Section: Judgements Of Difficulty Depend On Central Cues Such As Objmentioning

confidence: 99%

Mutual relationships between the levels and changes in interest, self-efficacy, and perceived difficulty during a task

Nuutila¹,

Tapola²,

Tuominen³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…This transition to the technology will help to extract more information that will be used as based for another type of learning it is an evolution process [56] that which climax is codification, by the subjects, critical thinking aspects, social and academic skills [57]. A good example of this is that the active learning will spread motivation, more and more, dealing and managing difficulties before the problems [58] increase in the way that people can develop the attitudes of curiosity and research to aim new answers from new questions [59]. In higher education, we will see active learning becoming an everyday life practice, where students exchange experiences, research approaches, and visit more degree programs [60], working and knowing better than ever, but each case is a case, and the knowledge world is very diverse, so what we know about the future?…”

Section: Conclusion and Future Trendsmentioning

confidence: 99%

Introductory Chapter: Active Learning—Beyond the Future

Brito¹

2019

Active Learning - Beyond the Future

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Training-group (an interactive technique where people learn from each other, the bestknown technique is the psychodrama) [24]. 2. Team-building (use of intervention different types that enhance social relationships and clarify the roles of group members, one of the known techniques is outdoor) [25]. 3. Delphi technique (use of an experts group to compare unstructured or individual groups) [26]. 4. Technique of help interview/consultation (consultation process-technique of psychological interview) [27]. 5. Force-field analysis technique (the technique of events diagnosis for results optimization) [28]. 6. Confrontation group technique (a technique that means having the courage to tell a person what they have seen or heard, to show that they are worried about them and to suggest that they are willing to help) [29]. 7. Data feedback technique (data feedback-ability to give and receive opinions, criticisms and suggestions about our attitudes, behaviors, and/or performances, with the purpose of reorienting and/or stimulating a particular individual or group action) [30]. 8. Third-party technique (the third party-is a procedure for the resolution of controversies-is one of the alternative methods to classic judiciary litigation), [31].

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“…In the educational setting it is vital that student motivation is fostered, and that good performance is ensured [9]. Consequently, the importance of updating teaching methodologies has frequently been addressed.…”

Section: Introductionmentioning

confidence: 99%

The Limited Effect of Graphic Elements in Video and Augmented Reality on Children’s Listening Comprehension

et al. 2020

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There is currently significant interest in the use of instructional strategies in learning environments thanks to the emergence of new multimedia systems that combine text, audio, graphics and video, such as augmented reality (AR). In this light, this study compares the effectiveness of AR and video for listening comprehension tasks. The sample consisted of thirty-two elementary school students with different reading comprehension. Firstly, the experience, instructions and objectives were introduced to all the students. Next, they were divided into two groups to perform activities—one group performed an activity involving watching an Educational Video Story of the Laika dog and her Space Journey available by mobile devices app Blue Planet Tales, while the other performed an activity involving the use of AR, whose contents of the same history were visualized by means of the app Augment Sales. Once the activities were completed participants answered a comprehension test. Results (p = 0.180) indicate there are no meaningful differences between the lesson format and test performance. But there are differences between the participants of the AR group according to their reading comprehension level. With respect to the time taken to perform the comprehension test, there is no significant difference between the two groups but there is a difference between participants with a high and low level of comprehension. To conclude SUS (System Usability Scale) questionnaire was used to establish the measure usability for the AR app on a smartphone. An average score of 77.5 out of 100 was obtained in this questionnaire, which indicates that the app has fairly good user-centered design.

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Active teaching to manage course difficulty and learning motivation

Cited by 33 publications

References 47 publications

Mutual relationships between the levels and changes in interest, self-efficacy, and perceived difficulty during a task

Mutual relationships between the levels and changes in interest, self-efficacy, and perceived difficulty during a task

Introductory Chapter: Active Learning—Beyond the Future

The Limited Effect of Graphic Elements in Video and Augmented Reality on Children’s Listening Comprehension

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