فاعلية تصميم بيئة تعلم مصغر قائمة على نظرية العبء المعرفي في تنمية التحصيل المؤجل ومهارات التعلم الذاتي لدى طالبات جامعة طيبة
الكلمات المفتاحية:
التعلم المصغر، التعلم الإلكتروني ،التصميم التعليمي، التعلم الذاتي، العبء المعرفيالملخص
الأهداف: تصميم بيئة تعلم مصغر قائمة على نظرية العبء المعرفي لتنمية التحصيل المؤجل ومهارات التعلم الذاتي لدى طالبات جامعة طيبة، وقياس فاعليتها.
المنهجية: استخدمت الدراسة المنهج شبه التجريبي؛ وطُبِّقَت في الفصل الدراسي الأول من العام الجامعي (1441ه)؛ على عينة وتكونت من (13) طالبة من طالبات كلية التربية، واللاتي يدرسن مقرر التعلم الإلكتروني، وقد تم اختيارهن بطريقة عمدية. ولتحقيق أهداف الدراسة؛ طُبِّق مقياس مهارات التعلم الذاتي والاختبار التحصيلي الذي أعدته الباحثة.
النتائج: وقد أظهرت نتائج الدراسة وجود فاعلية لتصميم بيئة تعلم مصغر قائمة على نظرية العبء المعرفي في تنمية التحصيل لدى عينة الدراسة، إلا أن الفاعلية محدودة، بالإضافة إلى فاعليتها في بقاء أثر التحصيل، وعدم وجود فروق ذات دلالة إحصائية بين التطبيقين القبلي والبعدي في درجات مهارات مقياس التعلم الذاتي.
التوصيات: تطبيق الدراسة الحالية على عينة أكبر ومن مستويات جامعية أخرى ذات تخصصات مختلفة وعبر تطبيقات تعليمية أخرى داعمة. كما توصي الدراسة بإجراء دراسة نوعية تركز على فاعلية تصميم بيئة تعلم مصغر قائمة على التلعيب لدى طلاب التعليم العالي.
التنزيلات
المراجع
Ahmad, N., & Al-khanjari, Z. (2016). Effects of audio podcasts as a micro learning tool on instruction. E-Leader International Journal, 11(2). Retrieved from https://www.g-casa.com/conferences/vienna16/paper_pdf/Ahmad.pdf
Ahmed, R. (2018a). The impact of the interaction between learning aids types and the responsibilities of providing them with micro-learning environments by the mobile web in developing programming skills and usability for Education Technology students. Educational Technology - Studies and Research, 35, 201-278.
Ahmed, S. (2018b). Using Cognitive Load Theory strategies in teaching Psychology to develop and retain the skills of meditative thinking and self-esteem among students with visual disabilities at the secondary school level. Journal of the Faculty of Education - Assiut University, 34(5), 40-107.
Aitchanov, B., Satabaldiyev, A., & Latuta, K. (2013). Application of microlearning technique and Twitter for educational purposes. Journal of Physics: Conference Series, 423, 1-4. https://doi.org/10.1088/1742-6596/423/1/012044
Alabbasi, D. (2018). The Effects of learning from self-paced program built based on the worked example principle on high school students’ ability to solve complicated math problems compared to the traditional way of learning. Dirasat: Educational Sciences, 45(4), 204-214.
Alabbasi, M. (2015). The effect of different types of information flow and degrees of homeliness in virtual environments in achievement and the development of self-learning skills of students of the College of Education. Educational Technology - The Egyptian Association for Educational Technology, 25(4), 311-352.
Alharbi, M. (2015). Engagement in Learning in light of the different source of Cognitive load& order Cognitive Holding Power& level of Learned Helplessness Among secondary school students. Journal of Educational Sciences, 27(3), 461-488.
Al-Otaibi, K. (2017). The Effect of Hyper Annotations Modes in Electronic Learning Environments on Developing the Reading Comprehension Skills and Cognitive Load of Intermediate Grade Students. Unpublished master's thesis. Qassim University, Buraydah, Saudi Arabia.
Alqurashi, E. (2018). Creating a microlearning environment to facilitate retention of information: A three-step approach. Proceedings of the 41st Annual AECT, Kansas, United States.
Alsabab, A. (2016). Cognitive Load and its relationship of mental capacity according to the university students' levels. Journal of College of Education - Al-Mustansyriah University, 6, 139-184.
Al-Zboon, M., & Hamdi, N. (2017). The Effect of Teaching by Using (Moodle) On Improving Self-Learning Skills of Students of the University of Jordan. Dirasat: Educational Sciences, 44(Special Issue), 189-203.
Al-Zoubeidi, B., & Hamdi, N. (2017). The Level of Susceptibility to Self-Learning among the Students of the Faculty of Educational Sciences at the University of Jordan in the Light of Dealing with Modern Technological Innovations. Dirasat: Educational Sciences, 44, 43-61.
Al-Zu'obi, M. (2017). The Effect of Cognitive Load, Presentation Method, Organizing, and Presentation Period of Instructional Material in Multimedia Learning Environments on Remembrance. International Journal of Educational and Psychological Studies, 5, 189-218.
Ayres, P., & Paas, F. (2012). Cognitive load theory: New directions and challenges. Applied Cognitive Psychology, 26(6), 827-832.
Bolt, N. (2011). Academic Achievement. In S. Goldstein & J.A Naglieri (Eds), Encyclopedia of Child Behavior and Development. Boston, MA: Springer. https://doi.org/10.1007/978-0-387-79061-9
Brookfield, S. (2017). Self-directed learning. In K. Peppler (Ed.), The SAGE encyclopedia of out-of-school learning (Vol. 1, pp. 689-691). Thousand Oaks, CA: SAGE Publications Inc.
Buchem, I., & Henrike, B. (2010). Microlearning: A strategy for ongoing professional development. eLearning Papers, 21(7), 1-15.
Chong, Y., Wan, F., & Toh, S. (2012). Reducing cognitive load using RLOs with instructional strategies. International Journal of Scientific and Engineering Research, 3(8), 207-2I0.
Collins, A., & Halverson, R. (2018). Rethinking education in the age of technology: The digital revolution and schooling in America. New York: Teachers College Press.
Eroglu, M., & Ozbek, R. (2018). The investigation of the relationship between attitudes towards e-learning and self-directed learning with technology of secondary school students. International Online Journal of Educational Sciences, 10(5), 297-314.
Fisher, M., King, J., & Tague, G. (2001). Development of a self-directed learning readiness scale for nursing education. Nurse Education Today, 21(7), 516-525.
Garrison, D. (1997). Self-directed learning: Toward a comprehensive model. Adult Education Quarterly, 48(1), 18-33.
Hassan, N. (2012). The Effectiveness of using a web-based site in accordance with the constructivist and behavioral theory in developing self-learning skills and the trend towards it among students in educational technology. Journal of Arab studies in education and Psychology, 27(3), 12-51.
Hug, T. (2005). Micro learning and narration: Exploring possibilities of utilization of narrations and storytelling for the designing of "micro units" and didactical micro-learning arrangements. Proceedings of the 4th Media in Transition Conference, Cambridge, United States.
Hug, T. (2012). Microlearning. In N. Seel (Ed.), Encyclopedia of the sciences of learning (Vol. 5, pp. 2268-2271). New York, NY: Springer.
Isba, R. (2015). When I say … micro learning environment. Medical Education, 49(9), 859-860.
Iskandar, R. & Ibrahim, R. (2018). The effect of different types of presentation of digital video texts with Cognitive Load Theory on the achievement and attitude of students with the Human Rights curriculum. Educational Technology - Studies and Research, 35, 53-98.
Jaleel, S., & Anuroofa, O. (2017). A study on the relationship between self-directed learning and achievement in information technology of students at secondary level. Universal Journal of Educational Research, 5(10), 1849-1852.
Jalil, W. (2015). The effect of teaching according to the Cognitive Load Theory on the achievement of biochemistry, information retention and scientific and technological enlightenment among students of the Chemistry Department/ College of Education at Ibn Al-Haytham College of Pure Sciences. Egyptian Journal of Scientific Education, 18(4), 19-43.
Jomah, O., Masoud, A., Kishore, X., & Aurelia, S. (2016). Micro learning: A modernized education system. Broad Research in Artificial Intelligence and Neuroscience, 7(1), 103-110.
Kalyuga, S. (2011). Cognitive load theory: How many types of load does it really need? Educational Psychology Review, 23(1), 1-19.
Kamilali, D., & Sofianopoulou, C. (2013). Lifelong learning and web 2.0: Microlearning and self-directed learning. Proceedings of EduLearn13 Conference, Barcelona, Spain.
Kazem, S. (2009). Self-learning skills and knowledge explosion. Proceedings of the second scientific conference of the Faculty of Educational Sciences, The role of the Arab teacher in the era of cognitive flow, Jerash, The Hashemite Kingdom of Jordan.
Kerres, M. (2007). Microlearning as a challenge for instructional design. In T. Hug (Ed.), Didactics of Microlearning: Concepts, Discources and Examples (pp.98-109), Münster, German: Waxmann Verlag.
Kılıç, F. (2010). Structuring of knowledge and cognitive load. In G. Kurubacak & T. Yuzer (Eds.), Handbook of research on transformative online education and liberation: models for social equality (pp.370-382). Hershey, PA: Information Science Reference.
Lawrence, C. (2006). Take a load off: Cognitive considerations for game design. Proceedings of the 3rd Australasian conference on Interactive entertainment. Australia: Perth.
Mahmoud, I. (2016). Impact of Interaction between the Volume of Micro-Learning Content (Small -Medium -Large) and Level of Mental Capacity (Low -High) on Developing of Information Technology Department (ITD) Students' Immediate and Deferred Achievement of IT Concepts. Journal of Arab studies in education and Psychology, 70, 17-77.
Mansour, M. (2014). The effect of using virtual flow maps on developing visual thinking skills and reducing the cognitive load among students of professional diploma in Educational Technology. Journal of the College of Education - Assiut University, 30(4), 649-698.
Mohamed, A. (2012). The cognitive load and its relationship to learning style among a sample of university students: a predictive study. Journal of Education - Al-Azhar University, 151(3), 695-741.
Mohamed, H. M. (2016). The effectiveness of an enrichment program in science using blogs in developing e-learning and visual thinking skills for gifted students at the primary level. Egyptian Journal of Scientific Education, 19(2), 39-83.
Mohammed, G., Wakil, K., & Nawroly, S. (2018). The effectiveness of microlearning to improve students’ learning ability. International Journal of Educational Research Review, 3(3), 32-38.
Muhammad, N. (2017). The interaction between digital learning elements and methods of displaying iconic active content and their effect on developing self-learning skills and programming skills for university students. World of Education, 18(58), 1-69.
Muongmee, S. (2007). The role of lifelong learning and self-directed learning in educational reform in Thailand. Educational Journal of Thailand, 1(1), 33-42.
Örs, M. (2018). The self-directed learning readiness level of the undergraduate students of midwife and nurse in terms of sustainability in nursing and midwifery education. Sustainability, 10(10), 3574. https://doi.org/10.3390/su10103574
Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1-4.
Paas, F., Tuovinen, J., Tabbers, H., & Van Gerven, P. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63-71.
Paas, F., van Gog, T., & Sweller, J. (2010). Cognitive load theory: New conceptualizations, specifications, and integrated research perspectives. Educational Psychology Review, 22(2), 115-121.
Paduri, V., Suresh, N., Hashiyana, V., Nobert, J., Hamukoto, L., & Mwatilifange, S. (2017). Micro learning and microteaching strategy pragmatic to tertiary institutions using smart devices. Proceedings of the International Conference on Researches in Science and Technology, Hyderabad, India.
Quiroga, L., Crosby, M., & Iding, M. (2004). Reducing cognitive load. Proceedings of the 37th Hawaii International Conference on System Sciences, Big Island, Hawaii.
Rashid, T., & Asghar, H. (2016). Technology use, self-directed learning, student engagement and academic performance: Examining the interrelations. Computers in Human Behavior, 63, 604-612.
Rettger, E. (2017). Microlearning with mobile devices: Effects of distributed presentation learning and the testing effect on mobile devices. Unpublished doctoral dissertation, Arizona State University, Tempe, United States.
Rourke, A. (2007). Cognitive load theory, visual literacy and teaching design history. Proceedings of the ConnectED 2007 International Conference on Design Education, Sydney, Australia.
Shahrouri, E. (2016). The impact of Garrison’s Model of self-directed learning on improving academic self-concept for undergraduate students: AUE as a Model. European American Journals, 4(10), 36-45.
Sharaf Al-Din, N. (2008). The efficiency of a supposed compromise educational model in academic achievement and developing self - directed learning skills through favorite styles in learning for Graduate students. Journal of Psychological and Educational Research - Menoufia University, 23(2), 200-252.
Skalka, J., & Drlík, M. (2018). Conceptual framework of microlearning-based training mobile application for improving programming skills. In M. Auer & T. Tsiatsos (Eds.), Interactive Mobile Communication Technologies and Learning IMCL 2017 (pp.213-224). Cham, Switzerland: Springer.
So, H., & Lee, H. (2017). Analysis and implications of the research trend on microlearning. Korea Science & Art Forum, 30, 189–201.
So, H., Roh, S., Oh, J., Lee, H., Lee, J., & Ji, S. (2018). Adult learners' perspectives about microlearning: implications on the design of bite-sized content. Proceedings of the 26th International Conference on Computers in Education, Manila, Philippines.
Song, L., & Hill, J. (2007). A conceptual model for understanding self-directed learning in online Environments. Journal of Interactive Online Learning, 6(1), 27-42.
Stewart, R. (2007). Investigating the link between self-directed learning readiness and project-based learning outcomes: The case of international Masters Students in an engineering management course. European Journal of Engineering Education, 32(4), 453–465.
Sweller, J. (2003). Evolution of human cognitive architecture. In B. Ross (Ed.), The psychology of learning and motivation: Advances in research and theory (pp.215-266). New York, NY: Elsevier Science.
Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York, NY: Springer.
Uysal, M. (2013). Towards the use of a novel method: The first experiences on measuring the cognitive load of learned programming skills. Turkish Online Journal of Distance Education, 14(1),166-184.
van Merriënboer, J., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Educational Technology Research and Development, 53(3), 5-13.
van Mierlo, C., Jarodzka, H., Kirschner, F., & Kirschner, P. (2011). Cognitive Load Theory and E-Learning. In Z. Yan (Ed.), Encyclopedia of Cyberbehavior (pp.1178–1211). Hershey, PA: IGI Global.
Wang, Z., Luo, Y., & Qu, Y. (2017). Application of micro-lecture for engineering mechanics experimental teaching. International Journal of Innovation and Research in Educational Sciences, 4(2), 130-132.
Yang, H. (2013). New world, new learning: Trends and issues of e-learning. Procedia-Social and Behavioral Sciences, 77, 429–442.
Yeigh, T. (2014). Cognitive inhibition and cognitive load: A moderation hypothesis. International Journal for Cross-Disciplinary Subjects in Education, 5(3), 1744-1752.
Youssef, A., & Mohammed, K. (2018). A proposed training program in the light of the Cognitive Load Theory to develop teaching skills and mental motivation among student teachers in the Colleges of Education in Egypt and Saudi Arabia. Journal of the College of Education - Assiut University, 34(11), 318-377.
Zhamanov, A., & Zhamapor, M. (2013). Computer networks teaching by microlearning principles. Journal of Physics: Conference Series, 423(1), 6.
https://doi.org/10.1088/1742-6596/423/1/012028
Zufic, J., & Jurcan, B. (2015). Micro learning and EduPsy LMS. Proceedings of the 26th International Conference Central European Conference on Information and Intelligent Systems, Varaždin, Croatia.

