Session Information
Contribution
Coding Education and its Relationship with Computational Thinking:
Coding education has gained much attention especially over the last decade. During this period, many countries such as England and Turkey made coding courses mandatory in Primary School. In these courses, it is primarily aimed to enhance students’ problem solving, algorithmic thinking, collaboration, and critical thinking skills through coding. These critical skills have been recently aggravated under the broad term of computational thinking. International Society for Technology in Education (ISTE) (2015) listed “Computational Thinking” as one of the fundamental skills that today’s learners should possess among 6 other skills. ISTE called individuals possessing the ability of “Computational Thinking” as “Computational Thinker”. Computational thinking encompasses collaboration, creativity, problem solving, critical thinking, and algorithmic thinking (ISTE). Computational thinking has much to do with the way expert programmers think while solving authentic problems. There are a few ways of enhancing computational thinking, one of which is game-based learning.
Game-based Learning:
There are very few ways detailed to enhance coding skills such as unplugged activities and block based programming. Nevertheless, game-based learning stands out amongst these methods because it motivates students, enable authentic learning, support collaboration, and facilitate production (Can, 2003; Neimeyer, 2006; Tüzün, Yılmaz-Soylu, Karakuş, İnal & Kızılkaya, 2009). However, motivation in game-based learning need to be stressed. Malone (1980) lists four factors that have an impact on intrinsic motivation. These factors are control, fantasy, curiosity, and challenge. Quality (which could be described as usability, appropriateness to age, and visual quality) of games is among other factors affecting intrinsic motivation. A game without usable interface hampers interaction (Nielsen, 1993). In addition, today’s computer game players demand fascinating graphics from educational games like the one available in commercial games. Finally yet importantly, an appropriate game in education should not include elements of horror, sex, and violence.
Justification and Purpose of the Study:
It was clearly shown that using COTS (Commercial off the Shelf) games had remarkable benefits for coding education among other game-based coding education methods. The fact is that there are more feasible compared to games developed by students or teachers. Using COTS games for coding education means finding the most suitable commercial game and using it directly or with minor modifications. Nonetheless, finding the right COTS game for instructional objective at hand can be thorny. STEAM game store is a plausible option to help find the most suitable COTS games with the purpose of enhancing coding skills. It contains myriad COTS games developed so as to help enhance coding skills. Within this scope, this study aims to help both researchers and implementers in finding the right COTS game for enhancing coding skill. Since COTS games cannot be utilized without quality and providing intrinsic motivation, they were also examined in terms of quality and providing intrinsic motivation. To this end, the following research questions were formed to be answered.
Which COTS games have got a strong potential for coding education?
What are the features of the COTS games having strong potential for coding education?
How quality are COTS games obtained for enhancing coding skills?
To what extent do COTS games obtained for enhancing coding skills provide intrinsic motivation?
To what extent do COTS games enhance coding skills?
Method
This study is a descriptive study by nature. More specifically, a quantitative content analysis is employed. Data Sources: STEAM game store was preferred as data source. It is a digital game distribution platform founded in USA on 12 September 2003. There are 781 million games and over 125 million registered accounts in STEAM game store (Wikipedia, 2017). Data Collection Instruments: Four data collection tools developed by researchers within the scope of this study were utilized. First of them is “Game Information Form”. It includes name, price, release date, overall user reviews, genre, and minimum system requirements (MSR) of the games. Second data collection tool, “Game Computational Thinking Form” used to evaluate the game in relation to enhancing coding skills. It includes components of collaboration, problem solving, creativity, critical thinking, and algorithmic thinking. Third data collection tool, “Game Intrinsic Motivation Form”, evaluates COTS games respecting Malone’s (1980) intrinsic motivation variables, which are curiosity, control, fantasy, and challenge. Lastly, “Game Quality Form” includes three items. These are user friendliness, visual quality, and appropriateness to age. All data collection tools are 5 likert type with “1 being equal to absolutely disagree and 5 being equal to absolutely agree”. Process of the Study: First, four search terms were chosen, which are programming, coding, computing and algorithm. The number of games obtained through search conducted with four keywords was 1249 in the beginning. Obtained games were sorted by their overall user reviews. Only games that have got “overwhelmingly positive, very positive, positive, and mostly positive” comments were included in the study. After that, games containing elements of horror, violence and sex were eliminated. In this stage, the number of games was reduced to 29. In the final elimination process, experts separately filled in all three forms. Games reaching an average mean less than 3.5 out of 5 were discarded from the study, leaving a total of 6 games at hand. Data Analysis: To prove inter-rater reliability, three Spearman's rank correlation coefficients between two raters were calculated since date violated the normality assumption according to Shapiro-Wilk test. Spearman's rank correlation tests yielded the correlation magnitudes of 0.75, 0.67, and 0.82 for computational thinking, intrinsic motivation, and quality data collection forms, respectively. These correlation coefficients’ being strong, it could be contended that inter-rater reliability of rating results is ensured.
Expected Outcomes
This study aimed at determining the most suitable COTS games in STEAM game store for enhancing coding skills. A total of 6 COTS game amongst 1249 were selected for the study. The names of these games are 1) Human Resource Machine, 2) Algotica - Iteration 1, 3) Super Markup Man, 4) Screeps, 5) Glitchspace, and lastly 6) Cyber Sentinel. These final 6 COTS games are considerably inexpensive ones requiring a low minimum computer system; therefore, it could be inferred that their applicability to real learning environments such as computer laboratories are quite high. As for game quality and intrinsic motivation form, all obtained COTS games were found to be satisfactory for both in terms of game quality and intrinsic motivation. In addition to this, most of the games were found to be satisfactory in relation to problem solving and algorithmic thinking components of computational thinking concept. On this ground, it is contended that this study is beneficial by means of helping researchers and implementers in selecting proper COTS games for coding education. However, there are some drawbacks of the obtained games. Results of the study yielded that most obtained COTS games lacked of collaboration element. Because it is well known that collaboration is a key coding skill, games incorporating collaboration elements should be developed in further studies. This study is a descriptive one by nature, so experimental studies could be conducted in order to see whether COTS games contended to possess potential for coding education possess kinetic for it as well. Besides, in this study only two experts examined COTS games in STEAM game store. In the future studies, examination of games could be carried out by more experts.
References
Can, G. (2003). Perceptions of prospective computer teachers toward the use of computer games with educational features in education (Unpublished master's thesis). METU, Ankara, Turkey. ISTE (2015). Computational thinking leadership toolkit (First Edition). Retrieved from https://www.iste.org/explore/articleDetail?articleid=152&category=Solutions&article=Computational-thinking-for-all on July 9, 2017. Malone, T. W. (1980). What makes things fun to learn? A study of intrinsically motivating computer games. Palo Alto, CA: Xerox. Neimeyer, S. (2006). An examination of the effects of computer-assisted educational games on the student achievement (Unpublished master's thesis), The University of Houston, Clear Lake, USA. Nielsen, J. (1993). Usability engineering. Boston: AP Professional. STEAM (2017). STEAM store page. Retrieved from http://store.steampowered.com/ on July 23, 2017. Tüzün, H., Yılmaz-Soylu, M., Karakuş, T., İnal, Y., & Kızılkaya, G. (2009). The effects of computer games on primary school students’ achievement and motivation in geography learning. Computers & Education, 52(1), 68-77.4. Wikipedia. (2017). STEAM (software). Retrieved from https://en.wikipedia.org/wiki/Steam_(software) on July 10, 2017.
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