MATEMATİK ÖĞRETMEN ADAYLARININ MOBİL ÖĞRENME HAZIRBULUNUŞLUK DÜZEYLERİNİN İNCELENMESİ

Yıl 2019, , 566 - 587, 31.07.2019

Kübra Açıkgül

https://doi.org/10.17943/etku.566739

Cited By: 9

Öz

Bu
araştırmanın amacı matematik öğretmen adaylarının mobil öğrenmeye yönelik
hazırbulunuşluk düzeylerini belirlemektir. Ayrıca araştırmada matematik
öğretmen adaylarının mobil öğrenmeye yönelik hazırbulunuşluk düzeylerinin
cinsiyet, sınıf düzeyi, mobil teknoloji kullanma yeterliliği, mobil teknoloji
kullanma sıklığı, mobil teknolojileri matematiği öğrenme sürecinde kullanma
sıklığı, gelecekte mobil teknolojileri matematik derslerinde kullanma niyeti
değişkenleri açısından incelenmesi amaçlanmaktadır. Araştırma betimsel tarama
ve nedensel karşılaştırma yaklaşımının kullanıldığı ilişkisel tarama modelleri
ile gerçekleştirilmiştir. Araştırma 256 ilköğretim matematik öğretmen adayının
katılımıyla gerçekleştirilmiştir. Araştırmada veri toplama aracı olarak Kişisel
bilgi Formu ve 7’li likert tipte Mobil Öğrenmeye Yönelik Hazırbulunuşluk Ölçeği
kullanılmıştır. Araştırma sonucunda matematik öğretmen adaylarının mobil
öğrenmeye yönelik hazırbulunuşluklarının “Kısmen Katılıyorum” kategorisinde
olduğu belirlenmiştir. Matematik öğretmen adaylarının mobil öğrenmeye yönelik
hazırbulunuşluk düzeylerinin cinsiyet ve sınıf düzeyi değişkenleri açısından
istatistiksel olarak anlamlı düzeyde farklılaşmadığı görülmüştür. Diğer
taraftan araştırmada matematik öğretmen adaylarının mobil öğrenmeye yönelik
hazırbulunuşluk düzeylerinin mobil teknoloji kullanma yeterliliği, mobil
teknoloji kullanma sıklığı, mobil teknolojileri matematiği öğrenme sürecinde
kullanma sıklığı, gelecekte mobil teknolojileri matematik derslerinde kullanma
niyeti değişkenleri açısından istatistiksel olarak anlamlı düzeyde
farklılaştığı sonucuna ulaşılmıştır.

Anahtar Kelimeler

Matematik öğretmen adayı; mobil öğrenme; hazırbulunuşluk.

Kaynakça

• Abas, Z.W., Chng, L.P., & Mansor, N. (2009). A study on learner readiness for mobile learning at Open University Malaysia. IADIS International Conference Mobile Learning 2009 (pp. 151–157).
• Al-Adwan, A. S., Al-Madadha, A., & Zvirzdinaite, Z. (2018). Modeling students’ readiness to adopt mobile learning in higher education: An empirical study. International Review of Research in Open and Distributed Learning, 19(1), 221-241.
• Al-Fahad, F. N. (2009). Students' attitudes and perceptions towards the effectiveness of mobile learning in King Saud University, Saudi Arabia. The Turkish Online Journal of Educational Technology –TOJET, 8(2), 111-119.
• Al-Hujran, O., Al-Lozi, E., & Al-Debei, M. M. (2014). Get Ready to Mobile Learning: Examining Factors Affecting College Students' Behavioral Intentions to Use M-Learning in Saudi Arabia. Jordan Journal of Business Administration, 153(3301), 1-18.
• Alsancak-Sırakaya, D. ve Seferoğlu, S. S. (2018). Türkiye’nin mobil öğrenme karnesi: İmkânlar, fırsatlar ve sorunlarla ilgili bir inceleme. B. Akkoyunlu, A. İşman ve H. F. Odabaşı (Ed). Eğitim teknolojileri okumaları 2018, (34. Bölüm, ss. 492-513).
• Aljuaid, N. M. F., Alzahrani, M. A. R., & Islam, A. Y. M. (2014). Assessing mobile learning readiness in Saudi Arabia higher education: An empirical study. Malaysian Online Journal of Educational Technology, 2(2), 1-14.
• Alrasheedi, M., Capretz, L. F., & Raza, A. (2015). A systematic review of the critical factors for success of mobile learning in higher education (university students' perspective). Journal of Educational Computing Research, 52(2), 257-276.
• Ata, R., & Cevik, M. (2019). Exploring relationships between Kolb’s learning styles and mobile learning readiness of pre-service teachers: A mixed study. Education and Information Technologies. https://doi.org/10.1007/s10639-018-9835-y.
• Attewell, J. (2005). Mobile technologies and learning: A technology update and m-learning project summary. Learning and Skills Development Agency: United Kingdom. http://www.mlearning.org/.
• Bakhsh, M., Mahmood, A., & Sangi, N. A. (2015, December). An assessment of students' readines towards mobile learning at AIOU, Pakistan. In 2015 International Conference on Information and Communication Technologies (ICICT) (pp. 1-6). IEEE.
• Barati, M., & Zolhavarieh, S. (2012). Mobile learning and multi mobile service in higher education. International Journal of Information and Education Technology, 2(4), 297-299.
• Baş, M., & Sarıgöz, O. (2018). Determining the readiness levels of pre-service teachers towards mobile learning in classroom management. Educational Research and Reviews, 13(10), 382-390.
• Baysal, M., Armağan, C. ve Armağan, K. (2004). Türkiye’de öğretmenlerin mobil öğrenme algısını belirleyici faktörler üzerine bir araştırma. Eğitim ve Öğretim Araştırmaları Dergisi, 6(1), 161-174.
• Brown, TH. (2005) Towards a model for m-learning in Africa. International Journal on E-learning, 4(3), 299-315.
• Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3), 1054-1064.
• Choon-Keong, T., Ing, N.S. & Kean-Wah, L. (2013). Readiness for Mobile Learning at a Public University in East Malaysia. In Embi, M.A. & Nordin, N.M. (Eds.), Mobile Learning: Malaysian Initiatives & Research Findings (27-38). Bangi: Centre for Academic Advancement.
• Christensen, R., & Knezek, G. (2017). Readiness for integrating mobile learning in the classroom: Challenges, preferences and possibilities. Computers in Human Behavior, 76, 112-121.
• Chung, C. J., Hwang, G. J., & Lai, C. L. (2019). A review of experimental mobile learning research in 2010–2016 based on the activity theory framework. Computers & Education, 129, 1-13.
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
• Corbeil, J. R., & Valdes-Corbeil, M. E. (2007). Are you ready for mobile learning? Educause Quarterly, 30(2), 48-51.
• Corbeil, J. R., & Corbeil, M. E. (2011). Are we ready for mobile learning now? 2007 Mobile learning predictions revisited. Issues in Information System, 12(2), 142-152.
• Dennen, V. P., & Hao, S. (2014). Intentionally mobile pedagogy: The M-COPE framework for mobile learning in higher education. Technology, Pedagogy and Education, 23(3), 397-419.
• Drigas, A. & Pappas, M. A. (2015). A review of mobile learning applications for mathematics. International Journal of Interactive Mobile Technologies, 9(3),18-23.
• Eroğlu, M., Kaya, V. D., & Özbek, R. (2017). Can mobile learning be an opportunity for undergraduate teacher education?. European Journal of Social Science Education and Research, 4(6), 340-349.
• Fraenkel, J., Wallen, N. and Hyun, H.H. (2012). How to design and evaluate research in education (8th ed.). Boston: McGraw Hill.
• Gikas, J., & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. The Internet and Higher Education, 19, 18-26.
• Gökçearslan, Ş., Solmaz, E., & Kukul, V. (2017). Mobil öğrenmeye yönelik hazirbulunuşluk ölçeği: bir uyarlama çalışması. Eğitim Teknolojisi Kuram ve Uygulama, 7(1), 143-157.
• Gökdaş, İ., Torun, F., & Bağrıaçık, A. (2014). Öğretmen adaylarının cep telefonlarını eğitsel amaçlı kullanım durumları ve mobil öğrenmeye ilişkin görüşleri. Adnan Menderes Üniversitesi Eğitim Fakültesi Eğitim Bilimleri Dergisi, 5(2), 43-61.
• Graham, C. R., Burgoyne, N., Cantrell, P., Smith, L., St. Clair, L. and Harris, R. (2009). TPACK development in science teaching: Measuring the TPACK confidence of inservice science teachers. TechTrends, Special Issue on TPACK, 53(5), 70-79.
• Hair, J. F. Jr., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: P son/Prentice Hall.
• Hamat, A., Embi, M. A., & Hassan, H. A. (2012). Mobile learning readiness among UKM lecturers. Procedia-Social and Behavioral Sciences, 59, 406-410.
• Hamidi, H., & Chavoshi, A. (2018). Analysis of the essential factors for the adoption of mobile learning in higher education: A case study of students of the University of Technology. Telematics and Informatics, 35(4), 1053-1070.
• Hussin, S. , Manap, M., Amir, Z., & Krish, P. (2012). Mobile Learning Readiness among Malaysian Students at Higher Learning Institutes. Asian Social Science, 8(12), 276-283. doi:10. 5539/ass. v8n12p276.
• Hwang, G. J., & Chang, H. F. (2011). A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students. Computers & Education, 56(4), 1023-1031.
• Hwang, G. J., & Wu, P. H. (2014). Applications, impacts and trends of mobile technology-enhanced learning: a review of 2008–2012 publications in selected SSCI journals. International Journal of Mobile Learning and Organisation, 8(2), 83-95.
• Iqbal, S., & Bhatti, Z. A. (2015). An investigation of university student readiness towards m-learning using technology acceptance model. The International Review of Research in Open and Distributed Learning, 16(4), 83-103.
• İlçi, A. (2014). Investigation of pre-service teachers’ mobile learning readiness levels and mobile learning acceptance levels. Unpublished master’s thesis, METU, Ankara.
• Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford Press.
• Liaw, S. S., Hatala, M., & Huang, H. M. (2010). Investigating acceptance toward mobile learning to assist individual knowledge management: Based on activity theory approach. Computers & Education, 54(2), 446-454.
• Lin, J. S. C., & Hsieh, P. L. (2007). The influence of technology readiness on satisfaction and behavioral intentions toward self-service technologies. Computers in Human Behavior, 23(3), 1597-1615.
• Lin, H. H., Lin, S., Yeh, C. H., & Wang, Y. S. (2016). Measuring mobile learning readiness: scale development and validation. Internet Research, 26(1), 265-287.
• Mahat, J., Ayub, A. F. M., & Luan, S. (2012). An assessment of students’ mobile self-efficacy, readiness and personal innovativeness towards mobile learning in higher education in Malaysia. Procedia-Social and Behavioral Sciences, 64, 284-290.
• Martin, F., & Ertzberger, J. (2013). Here and now mobile learning: An experimental study on the use of mobile technology. Computers & Education, 68, 76-85.
• Matha, W., & Madarsha, K. B. (2013). Mobile learning acceptance among students of Ramkhamhaeng University. Doctoral dissertation, International Islamic University Malaysia.
• Nikou, S. A., & Economides, A. A. (2017). Mobile-based assessment: Investigating the factors that influence behavioral intention to use. Computers & Education, 109, 56-73.
• O'Bannon, B. W., & Thomas, K. M. (2015). Mobile phones in the classroom: Preservice teachers answer the call. Computers & Education, 85, 110-122.
• Özdamlı, F., & Uzunboylu, H. (2015). M‐learning adequacy and perceptions of students and teachers in secondary schools. British Journal of Educational Technology, 46(1), 159-172.
• Parasuraman, a. (2000). Technology Readiness Index (TRI): A Multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307-320.
• Park, Y. (2011). A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types. The International Review of Research in Open and Distributed Learning, 12(2), 78-102.
• Reychav, I., Dunaway, M., & Kobayashi, M. (2015). Understanding mobile technology-fit behaviors outside the classroom. Computers & Education, 87, 142-150.
• Schreurs, J., Moreau, R., & Ehlers, U. (2008). Measuring e-learning readiness. International Association of online engineering. https://doclib.uhasselt.be/dspace/bitstream/1942/8740/1/ICL08.pdf adresinden 12.03.2019 tarihinde alınmıştır.
• Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of educational research, 99(6), 323-338.
• Solmaz, E., & Gökçearslan, Ş. (2016). Mobil öğrenme: Lisansüstü tezlere yönelik bir içerik analizi çalışması. 10th International Computer and Instructional Technologies Symposium (ICITS), 16-18 May ,Rize University Rize, Türkiye.
• Sincuba, M. C. & John, M. (2017). An exploration of learners’ attitudes towards mobile learning technology-based ınstruction module and its use in mathematics education. International Electronic Journal Of Mathematics Education, 12(10), 845-858.
• Stone, A. (2004). Designing scalable, effective mobile learning for multiple technologies.In J. Attwell & C. Savill-Smith (Eds), Learning with mobile devices. London: Learning and Skills development Agency.
• Şad, S. N., & Göktaş, Ö. (2014). Preservice teachers' perceptions about using mobile phones and laptops in education as mobile learning tools. British journal of educational technology, 45(4), 606-618.
• Trifonova, A., & Ronchetti, M. K. (2003). Mobile learning e review of the literature. http://eprints.biblio.unitn.it/359/1/009.pdf adresinden 12.03.2019 tarihinden alınmıştır.
• Sung, E., & Mayer, R. E. (2012). Students' beliefs about mobile devices Vs. desktop computers in South Korea and the United States. Computers & Education, 59(4), 1328-1338.
• Taleb, Z., Ahmadi, A. & Musavi, M. (2014). The effect of m-learning on mathematics learning. Procedia - Social and Behavioral Sciences, 171, 83 – 89.
• Tezer, M., & Beyoğlu, D. (2018). How do preservice teachers’ readiness and attitudes towards mobile learning affect their acceptance of mobile learning systems?. TEM Journal, 7(4), 875-885.
• Wang, Y. S. & Wang, H. Y. (2008). Developing and validating an instrument for measuring mobile computing self-efficacy. CyberPsychology & Behavior, 11(4), 405-413.
• Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British journal of educational technology, 40(1), 92-118.
• Wu, W. H., Wu, Y. C. J., Chen, C. Y., Kao, H. Y., Lin, C. H., & Huang, S. H. (2012). Review of trends from mobile learning studies: A meta-analysis. Computers & Education, 59(2), 817-827.
• Yeap, J. A., Ramayah, T., & Soto-Acosta, P. (2016). Factors propelling the adoption of m-learning among students in higher education. Electronic Markets, 26(4), 323-338.