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Changes in functional brain activity patterns associated with computer programming learning in novices Kenji Hishikawa National Center of Neurology and Psychiatry (NCNP) Kenji Yoshinaga ( yoshinaga.kenji.3y@kyoto-u.ac.jp ) Kyoto University Graduate School of Medicine Hiroki Togo Kyoto University Graduate School of Medicine Takeshi Hongo Otsuma Women’s University Takashi Hanakawa Kyoto University Graduate School of Medicine Research Article Keywords: code comprehension, functional magnetic resonance imaging, program comprehension, the neuroscience of programming, programming learning Posted Date: November 8th, 2022 DOI: https://doi.org/10.21203/rs.3.rs-2239916/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/18 Abstract Background Computer programming, the process of designing, writing, and testing executable computer code, is an essential skill in numerous elds. A description of the neural structures engaged and modi ed during programming skill acquisition could help improve training programs and provide clues to the neural substrates underlying the acquisition of related skills. Methods Fourteen female university students without prior computer programing experience were examined by functional magnetic resonance imaging (fMRI) during the early and late stages of a 5-month ‘Computer Processing’ course. Brain regions involved in task performance and learning were identi ed by comparing responses to programming and control tasks during the early and late stages. Results The accuracy of programming task performance was signi cantly improved during the late stage. Various regions of the frontal, temporal, parietal, and occipital cortex as well as several subcortical structures (caudate nuclei and cerebellum) were activated during programming tasks. Brain activity in the right inferior frontal gyrus was greater during the late stage and signi cantly correlated with task performance. Learning was also associated with a rightward shift in laterality of the bilateral inferior frontal gyri. Although the left inferior frontal gyrus was also highly active during the programming task, there were no learning-induced changes in activity nor a signi cant correlation between activity and task performance. Conclusion Computer programming learning among novices induces functional neuroplasticity within the right inferior frontal gyrus but not the left inferior gyrus (Broca’s area). Introduction Advanced computer programs have revolutionized many elds, including telecommunications, scienti c research, commerce, entertainment, manufacturing, transportation, robotics, agriculture, military defense, and space exploration among others. Accordingly, computer programming is considered a necessary skill in many elds and a valuable academic discipline as it develops logical thinking. For these reasons, computer programming is being integrated into educational programs, often at the request of industry leaders. For instance, computer programming is a compulsory subject at the secondary education level in Page 2/18 the United Kingdom, Hungary, Russia, and Hong Kong (Yamanishi 2015), and the Japanese government recently introduced computer programming into elementary education. Previous studies have attempted to identify the speci c behavioral and psychological characteristics associated with programming skills. In the code recognition process, programmers may rely on the breadth- rst searching strategy (i.e., searching a data structure node with a given property) (Vessey 1985) or a goal-oriented, hypotheses-driven problem-solving strategy (Vessey 1985; Koenemann and Robertson 1991). Programmers may also use a speci c knowledge structure (Fix et al. 1993; Von Mayrhauser and Vans 1995); for instance, Fix and colleagues (Fix et al. 1993) suggested that expert programmers conduct symbolic operations that determine which inputs are fed into speci c parts of the program for processing. Moreover, programmers may use speci c patters of eye movements to review computer code (Uwano et al. 2006; Busjahn et al. 2015). In addition to such specialized cognitive processes and behaviors, programming skills may build upon rather conventional intellectual abilities such as executive functions, memory, language processing (syntax and vocabulary), mathematics, and reasoning. For successful applications, the computer programmer needs to understand computer language rst and foremost, which requires memory for codes and algorithm identi cation. These cognitive skills overlap with those needed to understand conventional spoken and written languages. Thus, learning computer programming is similar to learning a second language and so presumably depends on a partially overlapping set of neural structures and processes. Elucidating the neural substrates of computer programming skill acquisition could facilitate improved training methods and the further development of the requisite cognitive skills. Several functional magnetic resonance imaging (fMRI) studies investigating brain activities during a variety of programming tasks have demonstrated speci c activation of frontal and parietal lobes, including language-related areas (Siegmund et al. 2014; Floyd et al. 2017; Siegmund et al. 2017; Castelhano et al. 2019; Ikutani et al. 2021). In addition, a recent study examining both expert and novice programmers identi ed seven brain regions widely distributed in the frontal, parietal, and temporal cortices activated during programming tasks and associated with programming expertise (Ikutani et al. 2021). However, it remains unclear whether these brain regions are selectively recruited by expert programmers or are changed functionally by leaning (i.e., through neuroplastic processes underlying other forms of learning). To clarify this issue, it is necessary to measure brain activity repeatedly during programming learning. Herein, we investigate the brain activity patterns of novice computer programming students during programming tasks (requiring only answer selection by button press) performed under fMRI in the early phase and again in the late phase of a rst-ever computer programming course. We set three research questions (RQ): 1) Which regions of the brain show activity related to a programming task in programming learners? 2) Which regions of the brain show activity changes from the early to late phase of training due to learning? 3) How does the brain activity of a functionally altered brain region correlate with programming task performance? Programming learning can be regarded as the acquisition of a new written language, especially in beginners, so we speculated that the neural substrates would overlap with Page 3/18 those observed in second language learners, speci cally within the extended language network including inferior frontal gyrus and superior temporal gyrus (Ferstl et al. 2008). Methods Participants Fourteen female university students (mean age 18.6 years, range 18–20 years) without prior computer programing experience participated in the present study. All participants were right-handed according to self-report and of native Japanese ancestry recruited from the Faculty of Social Information Studies at Otsuma Women’s University, Tokyo, Japan. All had normal or corrected-to-normal vision, no hearing impairments, and normal cognitive abilities according to Raven’s Colored Progressive Matrices (mean score 34.5; range 29–36) (Basso et al. 1987). Participants gave written informed consent according to the protocol approved by the Ethics Committee of Otsuma Women’s University (29-002-2) and the National Center of Neurology and Psychiatry (A2017-021). Experimental design All participants took a 5-month programming class using the “Processing” application (https://processing.org/) at Otsuma Women’s University. Processing is a Java-based exible software package designed for learning how to code programs for the visual arts. Tens of thousands of students, artists, designers, researchers, and hobbyists use Processing for learning and prototyping. The participants learned the concepts of programming and how to produce graphics and animation during the programming class. The participants were examined by fMRI twice, once during the mid-term period and again during the last term of the programming class. We employed a conventional task–fMRI design with alternating blocks of experimental (programming) tasks and control tasks. The experimental tasks were three types of programming-related problems (Fig. 1): predicting the output of code execution (code execution), completing an imperfect code (code completion), and nding programming “bugs” (bug nding). For the code execution task, the participants read a complete source code and predicted the output if executed (Fig. 1A). For the code completion task, the participants read a source code with a blank section and chose an appropriate option to ll in the blank (Fig. 1B). For the bug nding task, participants detected and counted bugs in a source code (Fig. 1C). In the control task, participants were asked to count the appearance of speci c words in a nonsense code (Fig. 1D) produced by shu ing the source code used for the experimental task; hence, the same sets of words were used in both source and nonsense codes. In all tasks, the participants were asked to read visually presented codes and select one of three or four options by a button press within 20 seconds. All participants completed 40 experimental (the code execution task: 19; the code completion task: 10; the bug nding task: 11) and 40 control blocks presented over 6 runs. MRI data acquisition Page 4/18
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