Procedural versus content‐related hints for word problem solving: an exploratory study

Kock, Willem D. de; Harskamp, Evert

doi:10.1111/jcal.12148

Cited by 4 publications

(5 citation statements)

References 39 publications

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“…Logged data from an online geometry task developed by the Center for Educational Technology (Israel), where fifth- and sixth-grade students were asked to construct, measure and transform geometrical objects, was used to portray patterns of problem solving (Leiba, 2010). Within the context of studying feedbacks in mathematics, log files were used in different settings to measure students' learning while getting different types of feedback (de Kock & Harskamp, 2016; Gal & Hershkovitz, 2019).…”

Section: Introductionmentioning

confidence: 99%

Students’ Activity in an Online Learning Environment for Mathematics: The Role of Thinking Levels

Haleva

Hershkovitz

Tabach

2020

Journal of Educational Computing Research

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Understanding students’ behavior while solving tasks at various levels is essential for the support educators may provide to students. The current study reports on a large-scale exploration of students' activity in an online learning environment for mathematics, while comparing between lower-order thinking (LOT) and higher-order thinking (HOT) applets, and between grade levels. We analyzed log files of N = 32,581 5th- and 6th-grade students from all over Israel (a full sample of users in the studied platform), specifically comparing scores, completion rates, completion times, and repetition levels in LOT and HOT applets. Using within-subject and between-subject t tests, we found that students' performance and completion rate on the LOT applets were overall higher than those of the HOT applets, which, combined with other findings, may point to meta-cognitive or motivational processes involved. We also point out to the high rates of students' manipulation of the system in a way that allow them to increase their score. Finally, we found that the various measures we used to characterize students' online activity are not necessarily strongly correlated with each other. These findings will help teachers to take informed decisions regarding the incorporation of digital learning environments in their classrooms.

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Section: Introductionmentioning

confidence: 99%

Students’ Activity in an Online Learning Environment for Mathematics: The Role of Thinking Levels

Haleva

Hershkovitz

Tabach

2020

Journal of Educational Computing Research

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“…Table 3 Learning Analytics Approach in Mathematics Purpose of Application Author (Year) Improve the quality of teaching (n=17) (Balasooriya et al, 2018;Bertacchini et al, 2018;D. Kim et al, 2018;Gal et al, 2018;John et al, 2018;de Kock & Harskamp, 2016; D. R. Kim et al, 2016;Hue et al, 2015;Kickmeier-Rust, Hillemann, & Albert, 2014;Laakso & Kaila, 2018;Molenaar & Knoop-van Campen, 2018;Quinn et al, 2015;Ruipérez-valiente et al, 2015;San Pedro et al, 2017b;Sivaranjani et al, 2015;Smith et al, 2016;Viswanathan & Vanlehn, 2018) Make prediction of students (n=12) (B, Laroussi, & Benghezala, 2015;Cohen, 2017;Dani & Nasser, 2016;Duzhin & Gustafsson, 2018;Roberts et al, 2016;Román-González et al, 2018;Romero-Zaldivar et al, 2012;San Pedro et al, 2017b;Tomkin et al, 2018;Xing, Chen, Stein, & Marcinkowski, 2017b;Xing, Guo, et al, 2015;Xing, Wadholm, et al, 2015) Students behaviour (n=1) (Chu, Chen, & Tsai, 2017) Besides, LA in Mathematics education is also applied in helping teachers make a prediction of student achievement and make student drop out prediction in learning. The ability of LA to give this prediction greatly benefited Mathematics education in helping teachers develop a powerful and effective strategy to avoid dropping out among students and assessing the quality of teaching.…”

Section: Resultsmentioning

confidence: 99%

Learning Analytics in Mathematics: A Systematic Review

Ramli¹,

Maat²,

Khalid³

2019

IJARPED

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Learning analytics (LA) is a useful approach in helping teachers to interpret the data obtained from students. Applying LA in Mathematics is also an effective approach for teachers to understand their students in depth. The objective of this systematic review is to look at LA applications and their benefits in teaching and learning Mathematics. Systematic review allows researcher to perform a clear examination of LA and Mathematics using systematic and explicit methods. The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) approaches that cover resources from Scopus and Web of Science are applied in implementing a systematic review process, selection criteria and exceptions. As a result, 30 studies which related to LA and Mathematics have been reviewed. Review findings show that the LA approach in Mathematics is frequently applied in improving the quality of the teaching and learning process. In this context, the improvement of the quality of teaching is seen through the improvement of the quality of learning materials, the ability to see the development of learning, and the improvement of student attitudes and behaviors towards Mathematics. LA's benefits in Mathematics education allow teachers to predict student achievement and the risk of dropout of students in learning. Proposed future studies should highlight qualitative studies or mixed methods in support of LA application in Mathematics. Applying a game-based approach (GBL) that has the potential to make the learning process more positive and effective by applying technology is an approach that can be explored in leveraging LA in Mathematics.

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“…This result is also shown for specific feedback strategies. For example, de Kock and Harskamp (2016) showed for word problems that students were able to solve more tasks if the hints include not only procedural knowledge but link it to the given contents. Also in view of mathematical problem solving, Attali (2015) could show that the provision of hints after a wrong answer led in multimedia environments to a better performance of students compared to a group that did not receive hints after a wrong entry.…”

Section: Digital Feedbackmentioning

confidence: 99%

“…• Hints: For each task, the students can retrieve up to three hints which aim to guide and to structure student's working process (cf. Shute, 2008;de Kock and Harskamp (2016)). Following Shute (2008), hints can be seen as a form of elaborate feedback.…”

Section: The Digital Tool Mathcitymapmentioning

confidence: 99%

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How digital tools support the validation of outdoor modelling results

2023

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Mathematical modelling addresses numerous demands of modern mathematics education: The learning of mathematics is directly linked to reality and hence to real objects. At the same time, these tasks are very challenging for students, especially when their own solution process needs to be validated and refined. Studies even show that some students do not validate their results at all. Recent research has shown that digital tools can enhance the support of modelling activities in different ways. In this paper, we take the modelling step of validation into a deeper account and explore the potential of MathCityMap, a digital tool for outdoor mathematics education. Hereby, its automatic solution validation by means of a predefined interval and assessment of the result’s quality are taken into consideration. The modelling activities of secondary school students are compared on a quantitative and qualitative level – half of the students working with the MathCityMap app and half of them solving the tasks without any digital support. Based on the quantitative results, we can see that the app functionalities for elaborative feedback are used to varying degrees: While student groups frequently access the hints, the sample solution is hardly accessed. Moreover, our analysis can show the value of corrective app feedback. Student groups that used the app solved a comparable number of problems, but failed significantly less often than student groups that worked on math trails without the app. The qualitative results show that in particular the solution validation forces the students to proceed with a second run in the modelling cycle if a result is valued as wrong in the app. In addition, it helps the students to assess their own result in terms of its correctness. Based on the combined results, we draw conclusions about the app usage in mathematical modelling tasks.

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Procedural versus content‐related hints for word problem solving: an exploratory study

Cited by 4 publications

References 39 publications

Students’ Activity in an Online Learning Environment for Mathematics: The Role of Thinking Levels

Students’ Activity in an Online Learning Environment for Mathematics: The Role of Thinking Levels

Learning Analytics in Mathematics: A Systematic Review

How digital tools support the validation of outdoor modelling results

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