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- Ternblad, Eva Maria, et al.
(författare)
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Do preschoolers ‘Game the system’? : a case study of children’s intelligent (Mis)use of a teachable agent based play-&-learn game in mathematics
- 2018
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Ingår i: Artificial Intelligence in Education : 19th International Conference, AIED 2018, Proceedings - 19th International Conference, AIED 2018, Proceedings. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783319938424 - 9783319938431 ; 10947 LNAI, s. 557-569
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Konferensbidrag (refereegranskat)abstract
- For learning to take place in digital learning environments, learners need to use educational software – more or less – as intended. However, previous studies show that some school children, instead of trying to learn and master a skill, choose to systematically exploit or outsmart the system to gain progress. But what about preschoolers? The present study explores the presence of this kind of behavioral patterns among preschoolers who use a teachable agent-based play-&-learn game in early math. We analyzed behavioral data logs together with interviews and observations. We also analyzed action patterns deviating from the pedagogical design intentions in terms of non-harmful gaming, harmful gaming, and wheel-spinning. Our results reveal that even if pedagogically not intended use of the game did occur, harmful gaming was rare. Interestingly, the results also indicate an unexpected awareness in children of what it means to learn and to teach. Finally, we present a series of possible adjustments of the used software in order to decrease gaming-like behavior or strategies that signalize insufficient skills or poor learning.
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| 2. |
- Cukurova, Mutlu, et al.
(författare)
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An analysis framework for collaborative problem solving in practice-based learning activities : A mixed-method approach
- 2016
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Ingår i: Proceedings of LAK '16 6th International Conference on Learning Analytics and Knowledge. - New York, New York, USA : ACM Digital Library. ; , s. 84-88
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Konferensbidrag (refereegranskat)abstract
- Systematic investigation of the collaborative problem solving process in open-ended, hands-on, physical computing design tasks requires a framework that highlights the main process features, stages and actions that then can be used to provide 'meaningful' learning analytics data. This paper presents an analysis framework that can be used to identify crucial aspects of the collaborative problem solving process in practice-based learning activities. We deployed a mixed-methods approach that allowed us to generate an analysis framework that is theoretically robust, and generalizable. Additionally, the framework is grounded in data and hence applicable to real-life learning contexts. This paper presents how our framework was developed and how it can be used to analyse data. We argue for the value of effective analysis frameworks in the generation and presentation of learning analytics for practice-based learning activities.
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| 3. |
- Cukurova, Mutlu, et al.
(författare)
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Diagnosing collaboration in practice-based learning : Equality and Intra-individual variability of physical interactivity
- 2017
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Ingår i: Data Driven Approaches in Digital Education. - Cham : Springer. ; , s. 30-42
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Konferensbidrag (refereegranskat)abstract
- Collaborative problem solving (CPS), as a teaching and learning approach, is considered to have the potential to improve some of the most important skills to prepare students for their future. CPS often differs in its nature, practice, and learning outcomes from other kinds of peer learning approaches, including peer tutoring and cooperation; and it is important to establish what identifies collaboration in problem-solving situations. The identification of indicators of collaboration is a challenging task. However, students physical interactivity can hold clues of such indicators. In this paper, we investigate two non-verbal indexes of student physical interactivity to interpret collaboration in practice-based learning environments: equality and intra-individual variability. Our data was generated from twelve groups of three Engineering students working on open-ended tasks using a learning analytics system. The results show that high collaboration groups have member students who present high and equal amounts of physical interactivity and low and equal amounts of intra-individual variability.
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| 4. |
- Luckin, Rose, et al.
(författare)
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How Do We Unleash AIEd at Scale to Benefit All Teachers and Learners?
- 2017
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Ingår i: Artificial Intelligence in Education. - : Springer. ; , s. 665-667
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Konferensbidrag (refereegranskat)abstract
- The application of artificial intelligence to education (AIEd) has been the subject of academic research for more than 30 years, a period during which much technical progress has been made, but few in-roads into mainstream education have been achieved. With the upsurge of interest in AI in general and increasingly in AI for education in particular, what role could and should the AIED research community play?
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| 5. |
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| 6. |
- Spikol, Daniel, et al.
(författare)
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Exploring the interplay between human and machine annotated multimodal learning analytics in hands-on STEM Activities
- 2016
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Ingår i: Proceedings of LAK '16 6th International Conference on Learning Analytics and Knowledge. - New York, New York, USA : ACM Digital Library. ; , s. 522-523
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Konferensbidrag (refereegranskat)abstract
- This poster explores how to develop a working framework for STEM education that uses both human annotated and machine data across a purpose-built learning environment. Our dual approach is to develop a robust framework for analysis and investigate how to design a learning analytics system to support hands-on engineering design tasks. Data from the first user tests are presented along with the framework for discussion.
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| 7. |
- Ternblad, Eva Maria, et al.
(författare)
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Far from success – Far from feedback acceptance? The influence of game performance on young students’ willingness to accept critical constructive feedback during play
- 2020
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Ingår i: Artificial Intelligence in Education- 21st International Conference, AIED 2020, Proceedings, Part I. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783030522360 ; 12163 LNAI, s. 537-548
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Konferensbidrag (refereegranskat)abstract
- In a learning situation, feedback is of great importance in order to help a student to correct a possible misconception. However, previous research shows that many students tend to avoid feedback regarding failures, including critical constructive feedback (CCF) that is intended to support and guide them. This is especially true for lower-achieving students, who might perceive feedback as an ego-threat, and therefore protect themselves by neglecting it. However, it has been shown that such neglect can be suppressed by using teachable agents (TA’s). Another, but less studied factor that influences feedback acceptance is the degree or extent of failure when trying to solve a task. The present study explores if and how momentary performance levels influence middle school students’ willingness to accept CCF when playing an educational game in history – with or without a TA. On the basis of teacher assessments of the students’ general skills, data logs and analyses of sequential patterns, we concluded that the willingness to accept CCF differs between students, but also between conditions and situations. One major finding is that a TA supports the students to more readily embrace CCF, even if the effect is larger for lower-achieving students. Another finding is that indications of being far from succeeding, such as low success rates or repeated trials and revisions, have a negative impact on feedback acceptance, even if a TA mitigates some of this influence. The implications of these results are discussed in relation to meta-cognitive aspects of learning and to educational software design.
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