%0 Journal Article %1 Hooshyar2021Gaming %A Hooshyar, Danial %A Pedaste, Margus %A Yang, Yeongwook %A Malva, Liina %A Hwang, Gwo-Jen %A Wang, Minhong %A Lim, Heuiseok %A Delev, Dejan %D 2021 %J Journal of Educational Computing Research %K Computational Problem Programming lehrerfortbildung, literacy, medienkompetenz,thinking!computational,Kompetenz, solving, %N 3 %P 383-409 %R 10.1177/0735633120965919 %T From Gaming to Computational Thinking: An Adaptive Educational Computer Game-Based Learning Approach %U https://doi.org/10.1177/0735633120965919 %V 59 %X Educational games have been increasingly used to improve students\' computational thinking. However, most existing games have focused on the theoretical knowledge of computational thinking, ignoring the development of computational thinking skills. Moreover, there is a lack of integration of adaptivity into educational computer games for computational thinking, which is crucial to addressing individual needs in developing computational thinking skills. In this study, we present an adaptive educational computer game, called AutoThinking, for developing students\' computational thinking skills in addition to their conceptual knowledge. To evaluate the effects of the game, we conducted an experimental study with 79 elementary school students in Estonia, where the experimental group learned with AutoThinking, while the control group used a traditional technology-enhanced learning approach. Our findings show that learning with the adaptive educational computer game significantly improved students\' computational thinking related to both conceptual knowledge and skills. Moreover, students using the adaptive educational computer game showed a significantly higher level of interest, satisfaction, flow state, and technology acceptance in learning computational thinking. Implications of the findings are also discussed.

@article{Hooshyar2021Gaming, abstract = {Educational games have been increasingly used to improve students\' computational thinking. However, most existing games have focused on the theoretical knowledge of computational thinking, ignoring the development of computational thinking skills. Moreover, there is a lack of integration of adaptivity into educational computer games for computational thinking, which is crucial to addressing individual needs in developing computational thinking skills. In this study, we present an adaptive educational computer game, called AutoThinking, for developing students\' computational thinking skills in addition to their conceptual knowledge. To evaluate the effects of the game, we conducted an experimental study with 79 elementary school students in Estonia, where the experimental group learned with AutoThinking, while the control group used a traditional technology-enhanced learning approach. Our findings show that learning with the adaptive educational computer game significantly improved students\' computational thinking related to both conceptual knowledge and skills. Moreover, students using the adaptive educational computer game showed a significantly higher level of interest, satisfaction, flow state, and technology acceptance in learning computational thinking. Implications of the findings are also discussed.}, added-at = {2021-09-19T18:40:37.000+0200}, author = {Hooshyar, Danial and Pedaste, Margus and Yang, Yeongwook and Malva, Liina and Hwang, Gwo-Jen and Wang, Minhong and Lim, Heuiseok and Delev, Dejan}, biburl = {https://www.bibsonomy.org/bibtex/2d15e3368ea7839166fd84634fd511cb1/steschum}, doi = {10.1177/0735633120965919}, file = {0735633120965919.pdf}, interhash = {2ca1d438cd5a3ea01832190c36b82414}, intrahash = {d15e3368ea7839166fd84634fd511cb1}, journal = {Journal of Educational Computing Research}, keywords = {Computational Problem Programming lehrerfortbildung, literacy, medienkompetenz,thinking!computational,Kompetenz, solving,}, number = 3, pages = {383-409}, timestamp = {2021-09-19T18:41:56.000+0200}, title = {From Gaming to Computational Thinking: An Adaptive Educational Computer Game-Based Learning Approach}, url = {https://doi.org/10.1177/0735633120965919}, volume = 59, year = 2021 }