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References
- Abdulsahib, R. H. (2021). Learning difficulties in mathematics and its relationship to cognitive failures among middle school students. Ilkogretim Online, 20(6), 2291-2325. https://doi.org/10.17051/ilkonline.2021.06.211
- Alyoussef, I. Y. (2022). Acceptance of a flipped classroom to improve university students’ learning: An empirical study on the TAM model and the unified theory of acceptance and use of technology (UTAUT). Heliyon, 8(12). https://doi.org/10.1016/j.heliyon.2022.e12529
- Auccahuasi, W., Santiago, G. B., Núñez, E. O., & Sernaque, F. (2018, December). Interactive online tool as an instrument for learning mathematics through programming techniques, aimed at high school students. In Proceedings of the 6th International conference on information technology: IoT and Smart City (pp. 70-76). https://doi.org/10.1145/3301551.3301580
- Austin, A. C., Hammond, N. B., Barrows, N., Gould, D. L., & Gould, I. R. (2018). Relating motivation and student outcomes in general organic chemistry. Chemistry Education Research and Practice, 19(1), 331-341. https://doi.org/10.1039/C7RP00182G
- Balreira, D. G., Silveira, T. L. D., & Wickboldt, J. A. (2022). Investigating the impact of adopting Python and C languages for introductory engineering programming courses. Computer Applications in Engineering Education, 31(1), 47-62. https://doi.org/10.1002/cae.22570
- Bascuñana, J., León, S., González-Miquel, M., González, E. J., & Ramírez, J. (2023). Impact of Jupyter Notebook as a Tool to enhance the learning process in Chemical Engineering Modules. Education for Chemical Engineers. https://doi.org/10.1016/j.ece.2023.06.001
- Bao, Y., Wang, G., & Sun, Z. (2021). Exploration and Research on Integrating Programming Education into Junior Middle School Mathematics Classroom. In Proceedings of CECNet 2021: The 11th International Conference on Electronics, Communications and Networks (CECNet), November 18-21, 2021 (Vol. 345, p. 356). IOS Press. https://doi.org/10.3233/FAIA210422
- Bertoletti, A., Cannistrà, M., Soncin, M., & Agasisti, T. (2023). The heterogeneity of Covid-19 learning loss across Italian primary and middle schools. Economics of Education Review, 95, 102435. https://doi.org/10.1016/j.econedurev.2023.102435
- Caccavale, F., Gargalo, C. L., Gernaey, K. V., & Krühne, U. (2023). SPyCE: A structured and tailored series of Python courses for (bio) chemical engineers. Education for Chemical Engineers, 45, 90-103. https://doi.org/10.1016/j.ece.2023.08.003
- Carević, M. M., Petrović, M., & Denić, N. (2019). Figurative Numbers Contribution in Perceiving the Legality in Numerous Strings Tasks and Long-term Memory of Numerous Data. EURASIA Journal of Mathematics, Science and Technology Education, 15(4), em1692. https://doi.org/10.29333/ejmste/103387
- Donnelly, R., & Patrinos, H. A. (2022). Learning loss during Covid-19: An early systematic review. Prospects, 51(4), 601-609. https://doi.org/10.1007/s11125-021-09582-6
- Doruk, B. K., Aktümen, M., & Aytekin, C. (2013). Pre-service elementary mathematics teachers’ opinions about using GeoGebra in mathematics education with reference to ‘teaching practices’. Teaching Mathematics and its Applications: An International Journal of the IMA, 32(3), 140-157. https://doi.org/10.1093/teamat/hrt009
- Fabic, G. V. F., Mitrovic, A., & Neshatian, K. (2018). Investigating the effects of learning activities in a mobile Python tutor for targeting multiple coding skills. Research and practice in technology enhanced learning, 13, 1-24. https://doi.org/10.1186/s41039-018-0092-x
- Fauzan, F., Ansori, R. A. M., Dannur, M., Pratama, A., & Hairit, A. (2023). The Implementation of the Merdeka Curriculum (Independent Curriculum) in Strengthening Students’ Character in Indonesia. Aqlamuna: Journal of Educational Studies, 1(1), 136-155. https://doi.org/10.58223/aqlamuna.v1i1.237
- Filgona, J., Sakiyo, J., Gwany, D. M., & Okoronka, A. U. (2020). Motivation in Learning. Asian Journal of Education and Social Studies, 10(4), 16–37. https://doi.org/10.9734/ajess/2020/v10i430273
- Firdaus, F., Kailani, I., Bakar, M. N. B., & Bakry, B. (2015). Developing critical thinking skills of students in mathematics learning. Journal of Education and Learning (EduLearn), 9(3), 226-236. https://doi.org/10.11591/edulearn.v9i3.1830
- Frunza, M, C. (2016). Chapter 2F - Non-Parametric Techniques. Academic Press, 2016, pp. 169-181. https://doi.org/10.1016/B978-0-12-804494-0.00012-7
- Fonseca, N. G., Macedo, L., & Mendes, A. J. (2016, June). CodeInsights: Monitoring programming students' progress. In Proceedings of the 17th International Conference on Computer Systems and Technologies 2016 (pp. 375-382). https://doi.org/10.1145/2983468.2983492
- Gül, Ş., & Köse, E. Ö. (2018). Öğretmen Adaylarının Protein Sentezine Yönelik Algıları: Öğrenme Güçlüğüne Karşı Önerilen Çözümler. Erzincan Üniversitesi Eğitim Fakültesi Dergisi, 20(1), 237-250. https://doi.org/10.17556/erziefd.307083
- Hevia, F, J., Vergara, L, S., Velásquez, A, D., & Calderón, D. (2021). Estimation of the fundamental learning loss and learning poverty related to COVID-19 pandemic in Mexico. International Journal of Educational Development, 88(1), 102515. https://doi.org/10.1016/j.ijedudev.2021.102515
- Hsiao, T. C., Chuang, Y. H., Chang, C. Y., Chen, T. L., Zhang, H. B., & Chang, J. C. (2023). Combining Building Block Process With Computational Thinking Improves Learning Outcomes of Python Programming With Peer Assessment. SAGE Open, 13(4), 21582440231217715. https://doi.org/10.1177/21582440231217715
- Inguva, P., Bhute, V. J., Cheng, T. N., & Walker, P. J. (2021). Introducing students to research codes: A short course on solving partial differential equations in Python. Education for Chemical Engineers, 36, 1-11. https://doi.org/10.1016/j.ece.2021.01.011
- Isaeni, N., & Nugraha, A. (2022). Teknologi Dalam Transformasi Pembelajaran Kurikulum Merdeka. Direktorat Guru Pendidikan Dasar, Kemendikbudristek. https://doi.org/10.4444/jisma.v2i6.736
- Jakubowski, M., Gajderowicz, T., & Patrinos, H. A. (2023). Global learning loss in student achievement: First estimates using comparable reading scores. Economics Letters, 232, 111313. https://doi.org/10.1016/j.econlet.2023.111313
- Karnalim, O., & Ayub, M. (2017). The use of python tutor on programming laboratory session: Student perspectives. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 327-336. http://dx.doi.org/10.22219/kinetik.v2i4.442
- Kong, Q., Siauw, T., & Bayen, A. (2020). Python programming and numerical methods: A guide for engineers and scientists. Academic Press. https://doi.org/10.1016/C2018-0-04165-1
- Koupritzioti, D., & Xinogalos, S. (2020). PyDiophantus maze game: Play it to learn mathematics or implement it to learn game programming in Python. Education and Information Technologies, 25(4), 2747–2764. https://doi.org/10.1007/s10639-019-10087-1
- Kozakai, R., Kobayashi, T., Wenxuan, Z., & Watanabe, Y. (2022). Tendency Analysis of Python Programming Classes for Junior and Senior High School Students. Procedia Computer Science, 207, 4603-4612. https://doi.org/10.1016/j.procs.2022.09.524
- Kuriki, M. (2021). Using Python and Google Colab to teach undergraduate microeconomic theory. International Review of Economics Education, 38, 100225. https://doi.org/10.1016/j.iree.2021.100225
- Lee, D. Y., & Chung, J. I. (2019). The effects of middle school mathematical statistics area and Python programming STEAM instruction on problem solving ability and curriculum interest. Journal of the Korea Academia-Industrial Cooperation Society, 20(4), 336-344. https://doi.org/10.5762/KAIS.2019.20.4.336
- Leifheit, L., Tsarava, K., Moeller, K., Ostermann, K., Golle, J., Trautwein, U., & Ninaus, M. (2019). Development of a Questionnaire on Self-concept, Motivational Beliefs, and Attitude Towards Programming. Proceedings of the 14th Workshop in Primary and Secondary Computing Education on - WiPSCE’19. https://doi.org/10.1145/3361721.3361730
- Ling, H. C., Hsiao, K. L., & Hsu, W. C. (2021). Can students’ computer programming learning motivation and effectiveness be enhanced by learning python language? A multi-group analysis. Frontiers in Psychology, 11, 600814. https://doi.org/10.3389/fpsyg.2020.600814
- Mhlongo, S., Mbatha, K., Ramatsetse, B., & Dlamini, R. (2023). Challenges, opportunities, and prospects of adopting and using smart digital technologies in learning environments: An iterative review. Heliyon. https://doi.org/10.1016/j.heliyon.2023.e16348
- Možina, M., & Lazar, T. (2018). Syntax-Based Analysis of Programming Concepts in Python. In Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II 19 (pp. 236-240). Springer International Publishing. https://doi.org/10.1007/978-3-319-93846-2_43
- Nurmuiza, I., Maonde, F., & Sani, A. (2015). The Effect of Motivation on Mathematics Learning Outcomes High school student. Jurnal Pendidikan Matematika, 6(2), 113-122. https://doi.org/10.36709/jpm.v6i2.2065
- Pabón, O. S., & Villegas, L. M. (2019). Fostering motivation and improving student performance in an introductory programming course: An integrated teaching approach. Revista EIA, 16(31), 65-76. https://doi.org/10.24050/reia.v16i31.1230
- Papadakis, S. (2020). Robots and Robotics Kits for Early Childhood and First School Age. International Association of Online Engineering.
- Peng, R., & Fu, R. (2021). The effect of Chinese EFL students’ learning motivation on learning outcomes within a blended learning environment. Australasian Journal of Educational Technology, 37(6), 61–74. https://doi.org/10.14742/ajet.6235
- Rais, D & Xuezhi, Z. (2023). Human cognitive: learning mathematics through Python programming to support students’ problem-solving skills. Anatolian Journal of Education, 8(2), 85-98. https://doi.org/10.29333/aje.2023.826a
- Ramli,I, S., Maat, S, M., & Khalid, F. (2019). Learning Analytics in Mathematics: A Systematics Review. International Journal Research in Progressive Education and Development, 8(4): 436-449. http://dx.doi.org/10.6007/IJARPED/v8-i4/6563
- Rodrigues, L., Toda, A. M., Oliveira, W., Palomino, P. T., Avila-Santos, A. P., & Isotani, S. (2021, March). Gamification works, but how and to whom? an experimental study in the context of programming lessons. In Proceedings of the 52nd ACM technical symposium on computer science education (pp. 184-190). https://doi.org/10.1145/3408877.3432419
- Sakharkar, S. (2023). Systematic Review: Analysis of Coding Vulnerabilities across Languages. Journal of Information Security, 14(4), 330-342. https://doi.org/10.4236/jis.2023.144019
- Santos, H., Batista, J., & Marques, R. P. (2019). Digital transformation in higher education: the use of communication technologies by students. Procedia Computer Science, 164, 123-130. https://doi.org/10.1016/j.procs.2019.12.163
- Saraswat, S., Keswani, B., Kulshrestha, R., Sharma, S., Verma, N., & Alam, S. (2022). Accuracy assessment of several machine learning algorithms for breast cancer diagnosis. Mathematical Statistician and Engineering Applications, 71(4), 12578-12587. https://doi.org/10.17762/msea.v71i4.2378
- Schacter, D. L. (1999). The seven sins of memory: Insights from psychology and cognitive neuroscience. American psychologist, 54(3), 182. https://doi.org/10.1037/0003-066X.54.3.182
- Sentance, S., & Csizmadia, A. (2017). Computing in the curriculum: Challenges and strategies from a teacher’s perspective. Education and information technologies, 22, 469-495. https://doi.org/10.1007/s10639-016-9482-0
- Suherman, S., & Vidákovich, T. (2022). Assessment of mathematical creative thinking: A systematic review. Thinking Skills and Creativity, 44, 101019. https://doi.org/10.1016/j.tsc.2022.101019
- Sweller, J., van Merriënboer, J. J., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational psychology review, 31, 261-292. https://doi.org/10.1007/s10648-019-09465-5
- Tabet, N., Gedawy, H., Alshikhabobakr, H., & Razak, S. (2016, July). From alice to python. Introducing text-based programming in middle schools. In Proceedings of the 2016 ACM Conference on innovation and Technology in Computer Science Education (pp. 124-129). https://doi.org/10.1145/2899415.2899462
- Takefuji, Y. (2023). An updated tutorial on reproducible PyPI applications for advancing chemometrics and boosting learner motivation. Chemometrics and Intelligent Laboratory Systems, 241, 104941. https://doi.org/10.1016/j.chemolab.2023.104941
- Tilak, J. B. (2021). COVID-19 and education in India: A new education crisis in the making. Social Change, 51(4), 493-513. https://doi.org/10.1177/00490857211050131
- Wainer, J., & Xavier, E. C. (2018). A controlled experiment on Python vs C for an introductory programming course: Students’ outcomes. ACM Transactions on Computing Education (TOCE), 18(3), 1-16. https://doi.org/10.1145/3152894
References
Abdulsahib, R. H. (2021). Learning difficulties in mathematics and its relationship to cognitive failures among middle school students. Ilkogretim Online, 20(6), 2291-2325. https://doi.org/10.17051/ilkonline.2021.06.211
Alyoussef, I. Y. (2022). Acceptance of a flipped classroom to improve university students’ learning: An empirical study on the TAM model and the unified theory of acceptance and use of technology (UTAUT). Heliyon, 8(12). https://doi.org/10.1016/j.heliyon.2022.e12529
Auccahuasi, W., Santiago, G. B., Núñez, E. O., & Sernaque, F. (2018, December). Interactive online tool as an instrument for learning mathematics through programming techniques, aimed at high school students. In Proceedings of the 6th International conference on information technology: IoT and Smart City (pp. 70-76). https://doi.org/10.1145/3301551.3301580
Austin, A. C., Hammond, N. B., Barrows, N., Gould, D. L., & Gould, I. R. (2018). Relating motivation and student outcomes in general organic chemistry. Chemistry Education Research and Practice, 19(1), 331-341. https://doi.org/10.1039/C7RP00182G
Balreira, D. G., Silveira, T. L. D., & Wickboldt, J. A. (2022). Investigating the impact of adopting Python and C languages for introductory engineering programming courses. Computer Applications in Engineering Education, 31(1), 47-62. https://doi.org/10.1002/cae.22570
Bascuñana, J., León, S., González-Miquel, M., González, E. J., & Ramírez, J. (2023). Impact of Jupyter Notebook as a Tool to enhance the learning process in Chemical Engineering Modules. Education for Chemical Engineers. https://doi.org/10.1016/j.ece.2023.06.001
Bao, Y., Wang, G., & Sun, Z. (2021). Exploration and Research on Integrating Programming Education into Junior Middle School Mathematics Classroom. In Proceedings of CECNet 2021: The 11th International Conference on Electronics, Communications and Networks (CECNet), November 18-21, 2021 (Vol. 345, p. 356). IOS Press. https://doi.org/10.3233/FAIA210422
Bertoletti, A., Cannistrà, M., Soncin, M., & Agasisti, T. (2023). The heterogeneity of Covid-19 learning loss across Italian primary and middle schools. Economics of Education Review, 95, 102435. https://doi.org/10.1016/j.econedurev.2023.102435
Caccavale, F., Gargalo, C. L., Gernaey, K. V., & Krühne, U. (2023). SPyCE: A structured and tailored series of Python courses for (bio) chemical engineers. Education for Chemical Engineers, 45, 90-103. https://doi.org/10.1016/j.ece.2023.08.003
Carević, M. M., Petrović, M., & Denić, N. (2019). Figurative Numbers Contribution in Perceiving the Legality in Numerous Strings Tasks and Long-term Memory of Numerous Data. EURASIA Journal of Mathematics, Science and Technology Education, 15(4), em1692. https://doi.org/10.29333/ejmste/103387
Donnelly, R., & Patrinos, H. A. (2022). Learning loss during Covid-19: An early systematic review. Prospects, 51(4), 601-609. https://doi.org/10.1007/s11125-021-09582-6
Doruk, B. K., Aktümen, M., & Aytekin, C. (2013). Pre-service elementary mathematics teachers’ opinions about using GeoGebra in mathematics education with reference to ‘teaching practices’. Teaching Mathematics and its Applications: An International Journal of the IMA, 32(3), 140-157. https://doi.org/10.1093/teamat/hrt009
Fabic, G. V. F., Mitrovic, A., & Neshatian, K. (2018). Investigating the effects of learning activities in a mobile Python tutor for targeting multiple coding skills. Research and practice in technology enhanced learning, 13, 1-24. https://doi.org/10.1186/s41039-018-0092-x
Fauzan, F., Ansori, R. A. M., Dannur, M., Pratama, A., & Hairit, A. (2023). The Implementation of the Merdeka Curriculum (Independent Curriculum) in Strengthening Students’ Character in Indonesia. Aqlamuna: Journal of Educational Studies, 1(1), 136-155. https://doi.org/10.58223/aqlamuna.v1i1.237
Filgona, J., Sakiyo, J., Gwany, D. M., & Okoronka, A. U. (2020). Motivation in Learning. Asian Journal of Education and Social Studies, 10(4), 16–37. https://doi.org/10.9734/ajess/2020/v10i430273
Firdaus, F., Kailani, I., Bakar, M. N. B., & Bakry, B. (2015). Developing critical thinking skills of students in mathematics learning. Journal of Education and Learning (EduLearn), 9(3), 226-236. https://doi.org/10.11591/edulearn.v9i3.1830
Frunza, M, C. (2016). Chapter 2F - Non-Parametric Techniques. Academic Press, 2016, pp. 169-181. https://doi.org/10.1016/B978-0-12-804494-0.00012-7
Fonseca, N. G., Macedo, L., & Mendes, A. J. (2016, June). CodeInsights: Monitoring programming students' progress. In Proceedings of the 17th International Conference on Computer Systems and Technologies 2016 (pp. 375-382). https://doi.org/10.1145/2983468.2983492
Gül, Ş., & Köse, E. Ö. (2018). Öğretmen Adaylarının Protein Sentezine Yönelik Algıları: Öğrenme Güçlüğüne Karşı Önerilen Çözümler. Erzincan Üniversitesi Eğitim Fakültesi Dergisi, 20(1), 237-250. https://doi.org/10.17556/erziefd.307083
Hevia, F, J., Vergara, L, S., Velásquez, A, D., & Calderón, D. (2021). Estimation of the fundamental learning loss and learning poverty related to COVID-19 pandemic in Mexico. International Journal of Educational Development, 88(1), 102515. https://doi.org/10.1016/j.ijedudev.2021.102515
Hsiao, T. C., Chuang, Y. H., Chang, C. Y., Chen, T. L., Zhang, H. B., & Chang, J. C. (2023). Combining Building Block Process With Computational Thinking Improves Learning Outcomes of Python Programming With Peer Assessment. SAGE Open, 13(4), 21582440231217715. https://doi.org/10.1177/21582440231217715
Inguva, P., Bhute, V. J., Cheng, T. N., & Walker, P. J. (2021). Introducing students to research codes: A short course on solving partial differential equations in Python. Education for Chemical Engineers, 36, 1-11. https://doi.org/10.1016/j.ece.2021.01.011
Isaeni, N., & Nugraha, A. (2022). Teknologi Dalam Transformasi Pembelajaran Kurikulum Merdeka. Direktorat Guru Pendidikan Dasar, Kemendikbudristek. https://doi.org/10.4444/jisma.v2i6.736
Jakubowski, M., Gajderowicz, T., & Patrinos, H. A. (2023). Global learning loss in student achievement: First estimates using comparable reading scores. Economics Letters, 232, 111313. https://doi.org/10.1016/j.econlet.2023.111313
Karnalim, O., & Ayub, M. (2017). The use of python tutor on programming laboratory session: Student perspectives. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 327-336. http://dx.doi.org/10.22219/kinetik.v2i4.442
Kong, Q., Siauw, T., & Bayen, A. (2020). Python programming and numerical methods: A guide for engineers and scientists. Academic Press. https://doi.org/10.1016/C2018-0-04165-1
Koupritzioti, D., & Xinogalos, S. (2020). PyDiophantus maze game: Play it to learn mathematics or implement it to learn game programming in Python. Education and Information Technologies, 25(4), 2747–2764. https://doi.org/10.1007/s10639-019-10087-1
Kozakai, R., Kobayashi, T., Wenxuan, Z., & Watanabe, Y. (2022). Tendency Analysis of Python Programming Classes for Junior and Senior High School Students. Procedia Computer Science, 207, 4603-4612. https://doi.org/10.1016/j.procs.2022.09.524
Kuriki, M. (2021). Using Python and Google Colab to teach undergraduate microeconomic theory. International Review of Economics Education, 38, 100225. https://doi.org/10.1016/j.iree.2021.100225
Lee, D. Y., & Chung, J. I. (2019). The effects of middle school mathematical statistics area and Python programming STEAM instruction on problem solving ability and curriculum interest. Journal of the Korea Academia-Industrial Cooperation Society, 20(4), 336-344. https://doi.org/10.5762/KAIS.2019.20.4.336
Leifheit, L., Tsarava, K., Moeller, K., Ostermann, K., Golle, J., Trautwein, U., & Ninaus, M. (2019). Development of a Questionnaire on Self-concept, Motivational Beliefs, and Attitude Towards Programming. Proceedings of the 14th Workshop in Primary and Secondary Computing Education on - WiPSCE’19. https://doi.org/10.1145/3361721.3361730
Ling, H. C., Hsiao, K. L., & Hsu, W. C. (2021). Can students’ computer programming learning motivation and effectiveness be enhanced by learning python language? A multi-group analysis. Frontiers in Psychology, 11, 600814. https://doi.org/10.3389/fpsyg.2020.600814
Mhlongo, S., Mbatha, K., Ramatsetse, B., & Dlamini, R. (2023). Challenges, opportunities, and prospects of adopting and using smart digital technologies in learning environments: An iterative review. Heliyon. https://doi.org/10.1016/j.heliyon.2023.e16348
Možina, M., & Lazar, T. (2018). Syntax-Based Analysis of Programming Concepts in Python. In Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II 19 (pp. 236-240). Springer International Publishing. https://doi.org/10.1007/978-3-319-93846-2_43
Nurmuiza, I., Maonde, F., & Sani, A. (2015). The Effect of Motivation on Mathematics Learning Outcomes High school student. Jurnal Pendidikan Matematika, 6(2), 113-122. https://doi.org/10.36709/jpm.v6i2.2065
Pabón, O. S., & Villegas, L. M. (2019). Fostering motivation and improving student performance in an introductory programming course: An integrated teaching approach. Revista EIA, 16(31), 65-76. https://doi.org/10.24050/reia.v16i31.1230
Papadakis, S. (2020). Robots and Robotics Kits for Early Childhood and First School Age. International Association of Online Engineering.
Peng, R., & Fu, R. (2021). The effect of Chinese EFL students’ learning motivation on learning outcomes within a blended learning environment. Australasian Journal of Educational Technology, 37(6), 61–74. https://doi.org/10.14742/ajet.6235
Rais, D & Xuezhi, Z. (2023). Human cognitive: learning mathematics through Python programming to support students’ problem-solving skills. Anatolian Journal of Education, 8(2), 85-98. https://doi.org/10.29333/aje.2023.826a
Ramli,I, S., Maat, S, M., & Khalid, F. (2019). Learning Analytics in Mathematics: A Systematics Review. International Journal Research in Progressive Education and Development, 8(4): 436-449. http://dx.doi.org/10.6007/IJARPED/v8-i4/6563
Rodrigues, L., Toda, A. M., Oliveira, W., Palomino, P. T., Avila-Santos, A. P., & Isotani, S. (2021, March). Gamification works, but how and to whom? an experimental study in the context of programming lessons. In Proceedings of the 52nd ACM technical symposium on computer science education (pp. 184-190). https://doi.org/10.1145/3408877.3432419
Sakharkar, S. (2023). Systematic Review: Analysis of Coding Vulnerabilities across Languages. Journal of Information Security, 14(4), 330-342. https://doi.org/10.4236/jis.2023.144019
Santos, H., Batista, J., & Marques, R. P. (2019). Digital transformation in higher education: the use of communication technologies by students. Procedia Computer Science, 164, 123-130. https://doi.org/10.1016/j.procs.2019.12.163
Saraswat, S., Keswani, B., Kulshrestha, R., Sharma, S., Verma, N., & Alam, S. (2022). Accuracy assessment of several machine learning algorithms for breast cancer diagnosis. Mathematical Statistician and Engineering Applications, 71(4), 12578-12587. https://doi.org/10.17762/msea.v71i4.2378
Schacter, D. L. (1999). The seven sins of memory: Insights from psychology and cognitive neuroscience. American psychologist, 54(3), 182. https://doi.org/10.1037/0003-066X.54.3.182
Sentance, S., & Csizmadia, A. (2017). Computing in the curriculum: Challenges and strategies from a teacher’s perspective. Education and information technologies, 22, 469-495. https://doi.org/10.1007/s10639-016-9482-0
Suherman, S., & Vidákovich, T. (2022). Assessment of mathematical creative thinking: A systematic review. Thinking Skills and Creativity, 44, 101019. https://doi.org/10.1016/j.tsc.2022.101019
Sweller, J., van Merriënboer, J. J., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational psychology review, 31, 261-292. https://doi.org/10.1007/s10648-019-09465-5
Tabet, N., Gedawy, H., Alshikhabobakr, H., & Razak, S. (2016, July). From alice to python. Introducing text-based programming in middle schools. In Proceedings of the 2016 ACM Conference on innovation and Technology in Computer Science Education (pp. 124-129). https://doi.org/10.1145/2899415.2899462
Takefuji, Y. (2023). An updated tutorial on reproducible PyPI applications for advancing chemometrics and boosting learner motivation. Chemometrics and Intelligent Laboratory Systems, 241, 104941. https://doi.org/10.1016/j.chemolab.2023.104941
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