Is My Game OK Dr. Scratch?

Troiano, Giovanni Maria; Snodgrass, Sam; Argımak, Erinç; Robles, Gregório; Smith, Gillian; Cassidy, Michael; Tucker‐Raymond, Eli; Puttick, Gillian; Harteveld, Casper

doi:10.1145/3311927.3323152

Cited by 31 publications

(12 citation statements)

References 63 publications

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“…While Dr. Scratch returns general information on the detected computational thinking concepts, LitterBox returns specific hints on how to proceed regarding detected smells and bug patterns. Therefore, Dr. Scratch might be particularly effective for extending programs according to computational thinking concepts [46] and LitterBox for repairing and improving programs [15]. LitterBox thus might support creating good example code, which is why in this paper we focus on this tool.…”

Section: Tool Support For Scratch Programsmentioning

confidence: 99%

Exploring Programming Task Creation of Primary School Teachers in Training

Greifenstein

Heuer

2023

Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education v. 1

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Introducing computational thinking in primary school curricula implies that teachers have to prepare appropriate lesson material. Typically this includes creating programming tasks, which may overwhelm primary school teachers with lacking programming subject knowledge. Inadequate resulting example code may negatively affect learning, and students might adopt bad programming habits or misconceptions. To avoid this problem, automated program analysis tools have the potential to help scaffolding task creation processes. For example, static program analysis tools can automatically detect both good and bad code patterns, and provide hints on improving the code. To explore how teachers generally proceed when creating programming tasks, whether tool support can help, and how it is perceived by teachers, we performed a pre-study with 26 and a main study with 59 teachers in training and the LitterBox static analysis tool for Scratch. We find that teachers in training (1) often start with brainstorming thematic ideas rather than setting learning objectives, (2) write code before the task text, (3) give more hints in their task texts and create fewer bugs when supported by LitterBox, and (4) mention both positive aspects of the tool and suggestions for improvement. These findings provide an improved understanding of how to inform teacher training with respect to support needed by teachers when creating programming tasks. CCS CONCEPTS• Social and professional topics → Software engineering education; K-12 education; • Software and its engineering → Visual languages.

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Section: Tool Support For Scratch Programsmentioning

confidence: 99%

Exploring Programming Task Creation of Primary School Teachers in Training

Greifenstein

Heuer

2023

Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education v. 1

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“…Dr. Scratch automatically analyzes programming tasks according to the above scoring rules and presents scores to show the quality level of programming projects. There have been many studies that have used Dr. Scratch to assess students' CT skills (e.g., Moreno-León & Robles, 2015a;Park & Shin, 2019;Troiano et al, 2019;Vourletsis & Politis, 2022). In addition, CT concepts in Brennan and Resnick's (2012) framework correspond with the Dr. Scratch scoring criteria: abstraction = CT practices, logical thinking = operator, synchronization = event, parallelism = parallelism, flow control = sequence and loop, user interactivity = conditional, and data representation = data (Ternik et al, 2017).…”

Section: Instrumentmentioning

confidence: 99%

“…Dr. Scratch scores CT on seven dimensions: abstraction corresponding to CT practices, logical thinking corresponding to operator, synchronization to event, parallelism to parallelism, flow control to sequence and loop, user interactivity to conditional, and data representation to data (Ternik et al, 2017). Besides, CT concepts have been widely evaluated through Dr. Scratch (Park & Shin, 2019; Troiano et al, 2019). For instance, Park and Shin (2019) revealed the effectiveness of Scratch for fostering CT concepts.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For instance, Park and Shin (2019) revealed the effectiveness of Scratch for fostering CT concepts. Troiano et al (2019) used Dr. Scratch to observe and analyze the development process of each CT dimension of students in STEM courses. Although Dr. Scratch can objectively evaluate CT concepts, the evaluation of Scratch projects does not accurately capture the acquisition of CT perspectives due to its high complexity and abstraction (Zhang & Nouri, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

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Using Epistemic Network Analysis to Explore Primary School Students’ Computational Thinking in Pair Programming Learning

Su,

Wang,

Liu

2023

Journal of Educational Computing Research

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Pair programming (PP) can help improve students’ computational thinking (CT), but the trajectory of CT skills and the differences between high-scoring and low-scoring students in PP are unknown and need further exploration. In this study, a total of 32 fifth graders worked on Scratch tasks in 16 pairs. The group discourse of three learning topics (comprising 9 projects) was collected. After the audio files were transcribed, 1,303 conversations were obtained. They were analyzed via Epistemic Network Analysis (ENA) Webkit, which can reveal the trajectory of students’ CT development via analyzing codes of discourse related to CT in PP. Three Scratch learning topics were assessed based on the Dr. Scratch platform to acquire the level of students’ CT and to determine the low- and high-scoring groups. Results indicated that CT concepts and CT practices were always closely related in PP and CT practices, and CT perspectives could be gradually and closely related after a long period of CT training. A significant difference between the two groups’ CT structures was found. The high-scoring group had more fragments of CT practice and connecting of CT perspectives, while the low-scoring group showed more fragments of CT concepts and expressing of CT perspectives. This research provides insights into cultivating primary school students’ CT using Scratch in the context of PP. The findings can provide suggestions for instructors to design instructional interventions to facilitate students’ CT skills via PP learning. Instructors can improve CT skills by guiding students to constantly ask questions, and specifying the role swap between driver and navigator in PP. Besides, instructors could give more consideration to the development of CT perspectives, and especially the ability to question.

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“…Such environments basically use visual or block‐based programming and adapt the design principle of games to minimize the complexity related to the syntax of programming languages. To allow automatic assessment of CT through these environments (i.e., Scratch projects), Troiano et al [27] employed a gamified web application called Dr. Scratch to detect bad programming habits that are common among students. One of the most prominent findings of their study was that while students' proficiency in parallelism, synchronization, and logic develops competently, the development of abstraction appears to be difficult.…”

Section: Related Researchmentioning

confidence: 99%

Effects of technology‐enhanced learning approaches on learners with different prior learning attitudes and knowledge in computational thinking

Hooshyar

2021

Comput Appl Eng Educ

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This study investigated the effect of two technology‐enhanced learning methods (an adaptive educational computer game vs. a PowerPoint presentation with multimedia) on learners with different prior learning attitudes and knowledge regarding skills, conceptual knowledge, and overall knowledge of computational thinking (CT). Data from 70 students aged 11–12 were analysed using factorial multivariate analysis of covariance and analysis of covariance. Our findings revealed that while effective in fostering conceptual knowledge of CT (such as sequence, loop, and conditional), the conventional technology‐enhanced learning approach falls short when it comes to promoting CT skills (such as pattern recognition and debugging). The game approach, however, could simultaneously promote CT skills and conceptual knowledge, leading to improvement in the overall knowledge of CT. Additional analysis showed that learners with different prior knowledge and learning attitudes made a higher improvement using the adaptive game in terms of skills, conceptual knowledge, and overall knowledge of CT, especially for medium and lower prior knowledge learners that did not have a very high prior learning attitude. Consequently, to promote CT in primary school students, educators can employ computer game approaches that not only can foster both skills and conceptual knowledge of CT but also more effectively assist students with lower prior learning attitudes and knowledge.

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Is My Game OK Dr. Scratch?

Cited by 31 publications

References 63 publications

Exploring Programming Task Creation of Primary School Teachers in Training

Exploring Programming Task Creation of Primary School Teachers in Training

Using Epistemic Network Analysis to Explore Primary School Students’ Computational Thinking in Pair Programming Learning

Effects of technology‐enhanced learning approaches on learners with different prior learning attitudes and knowledge in computational thinking

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