Dijital İş Birliği, Yetkinlik ve Topluluk: Yükseköğretim Öğrencileri ve Öğretim Üyelerinin Bakış Açıları

Year 2026, Volume: 16 Issue: 1 , 279 - 299 , 28.03.2026

Hakan İslamoğlu , Eda Bakır , Yasin Yalçın , Ömer Faruk Ursavaş

https://doi.org/10.18039/ajesi.1834728

https://izlik.org/JA46BE67PS

Abstract

Bu çalışma, hem öğrencilerin hem de öğretim elemanlarının deneyimlerine dayanarak, bulut tabanlı üretkenlik ve iş birliği yazılımlarının yükseköğretimde nasıl benimsendiğini ve kullanıldığını ayrıntılı biçimde incelemiştir. Nitel bir durum çalışması çerçevesinde yürütülen araştırmada, veriler 26 katılımcıdan (19 öğretmen adayı, 7 öğretim elemanı) yarı yapılandırılmış görüşmeler, alan notları ve üye-kontrolü geri bildirimleri yoluyla toplanmıştır. Veri analizi, Teknoloji Kabul Modeli ve Uygulama Toplulukları kuramlarıyla uyumlu açık kodlama ve kuramsal bütünleştirme tekniklerini içermiştir. Araştırma, teknoloji kabulü, dijital okuryazarlık, grup dinamikleri, araç-seçim mantığı ve öğrenme stratejileri gibi çok katmanlı süreçlerin birlikte işlediğini göstermiştir. Bulgular, katılımcıların bulut tabanlı araçları başlangıçta zorunluluktan, daha sonra ise algılanan faydalar ve kullanım kolaylığı nedeniyle benimsediğini ortaya koymuştur. Dijital okuryazarlık düzeyleri, kullanım kolaylığı algılarını büyük ölçüde etkilemiş; pandemi hem öğrenciler hem de öğretim elemanları için önemli bir dönüştürücü etken olarak ortaya çıkmıştır. Katılımcılar iş birliğini eşitlik, uyum ve ortak sorumluluğa dayanan ideal bir süreç olarak tanımlamalarına rağmen, uygulamada katkı dengesizliği yaygın bir durum olarak görülmüştür. Grup oluşumuna ilişkin tercihler—öğrencilerin homojen grupları, öğretim elemanlarının ise heterojen grupları tercih etmesi—iş birliğinin sosyal boyutunun teknolojik özelliklerden daha etkili olduğunu göstermektedir. Görev–araç uyumu ve alışkanlık, araç ve platform seçiminde temel belirleyiciler olarak öne çıkmış; katılımcılar üretken görevlerde bilgisayarları, hızlı iletişim ve küçük düzenlemelerde ise telefonları kullanma eğilimindedir. Video kaynakları, deneme-yanılma yaklaşımları ve akran desteği belirgin öğrenme stratejileri olarak görülmüş; pandemi bu öğrenme sürecini hızlandırmıştır. Sonuç olarak, bulut tabanlı iş birliği araçlarının benimsenmesi, bireysel teknoloji kabulü ile topluluk temelli sosyal öğrenme dinamiklerinin etkileşim içinde olduğu karmaşık bir sistemi içermektedir. Dijital dönüşümün sürdürülebilirliği için yalnızca teknik eğitimin değil, aynı zamanda güven inşasının, topluluk etkinliklerinin ve şeffaf iş birliği yapıların desteklenmesi önerilmektedir.

Keywords

bulut tabanlı iş birliği , uygulama toplulukları , dijital yetkinlik , yüksek öğrenim , teknoloji kabulü

Ethical Statement

Bu çalışma Recep Tayyip Erdoğan Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi tarafından SBA-2020-1194 koduyla desteklenmiştir.

Supporting Institution

Recep Tayyip Erdoğan Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi

Project Number

SBA-2020-1194

Digital Collaboration, Competence, and Community: Perspectives from Higher Education Students and Faculty

https://izlik.org/JA46BE67PS

Abstract

Cloud-based collaboration tools have been quickly adopted in higher education, often out of necessity. However, insights into how students and faculty experience and utilize these technologies remain limited. This study aimed to enhance understanding of their specific needs by highlighting similarities and differences in technology use between both participant groups. Conducted within a qualitative case study framework, data were collected from 26 participants (19 students and 7 faculty members) through semi-structured interviews, field notes, and member-checking feedback. Data analysis involved open coding and theoretical integration techniques aligned with the Technology Acceptance Model and Communities of Practice theories. The research showed that multi-layered processes such as technology acceptance, digital literacy, group dynamics, tool-selection logic, and learning strategies work together. Findings indicated that participants initially adopted cloud-based tools out of necessity, then adopted them for perceived benefits and ease of use. Digital literacy levels greatly influenced perceptions of ease of use; the pandemic emerged as a significant transformative factor for both students and faculty. Although participants described collaboration as an ideal process based on equality, harmony, and shared responsibility, an imbalance in contributions was common in practice. Preferences for group formation highlight that the social aspect of collaboration is more influential than technological features. While students favored homogeneous groups, faculty preferred heterogeneous ones. Task-tool compatibility and habitual use were key factors in choosing tools and platforms; participants tended to use computers for productive tasks and phones for quick communication and minor adjustments. Video resources, trial-and-error approaches, and peer support were prominent learning strategies, and the pandemic has accelerated this learning process. In conclusion, adopting cloud-based collaboration tools involves a complex system in which individual technology acceptance and community-based social learning dynamics interact. To sustain digital transformation, it is recommended to support not only technical training but also trust-building, community activities, and transparent collaboration structures.

Keywords

cloud-based collaboration , communities of practice , digital competence , higher education , technology acceptance

Ethical Statement

This study was supported by the Scientific Research Projects Coordination Unit of Recep Tayyip Erdoğan University under code SBA-2020-1194.

Supporting Institution

the Scientific Research Projects Coordination Unit of Recep Tayyip Erdoğan University

Project Number

SBA-2020-1194

References

• Akgün-Özbek, E., & Özkül, A. E. (2019). E-transformation in higher education and what it coerces for the faculty. In A. Elçi, L. L. Beith, & A. Elçi (Eds.), Handbook of Research on Faculty Development for Digital Teaching and Learning (pp. 355–378). IGI Global. https://doi.org/10.4018/978-1-5225-8476-6.ch018
• Alahmari, A. A. (2018). A mixed methods study of the implementation of collaborative technology tools for enhancing collaboration and student engagement in online learning: Faculty experiences and student perspectives [EdD, Illinois State University]. https://doi.org/10.30707/ETD2019.Alahmari.A
• Alexander, B., Ashford-Rowe, K., Barajas-Murphy, N., Dobbin, G., Knott, J., McCormack, M., Pomerantz, J., Seilhamer, R., & Weber, N. (2019). EDUCAUSE Horizon Report: 2019 Higher education edition. EDUCAUSE.
• Ali, Z., Gongbing, B., & Mehreen, A. (2018). Understanding and predicting academic performance through cloud computing adoption: A perspective of technology acceptance model. Journal of Computers in Education, 5(3), 297–327. https://doi.org/10.1007/s40692-018-0114-0
• Amhag, L., Hellström, L., & Stigmar, M. (2019). Teacher educators’ use of digital tools and needs for digital competence in higher education. Journal of Digital Learning in Teacher Education, 35(4), 203–220. https://doi.org/10.1080/21532974.2019.1646169
• Bagozzi, R. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254. https://doi.org/10.17705/1jais.00122
• Brame, C. J. (2016). Effective educational videos: Principles and guidelines for maximizing student learning from video content. CBE—Life Sciences Education, 15(4), es6. https://doi.org/10.1187/cbe.16-03-0125
• Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
• Cahill, J. L. (2014). University professors’ perceptions about the impact of integrating Google applications on students’ communication and collaboration skills. Journal of Research Initiatives, 1(2). https://digitalcommons.uncfsu.edu/jri/vol1/iss2/7
• Corbin, J. M., & Strauss, A. L. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory (Fourth edition). SAGE.
• Cosgrove, J., & Cachia, R. (2025). DigComp 3.0 European digital competence framework—Fifth edition (5th ed.). Publications Office of the European Union. https://data.europa.eu/doi/10.2760/0001149
• Cox, A. (2005). What are communities of practice? A comparative review of four seminal works. Journal of Information Science, 31(6), 527–540. https://doi.org/10.1177/0165551505057016
• Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design (Fourth edition). SAGE.
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
• Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of research on Technology in Education, 42(3), 255-284. https://doi.org/10.1080/15391523.2010.10782551
• Ferrari, A. (2013). DIGCOMP: A framework for developing and understanding digital competence in Europe. Publications Office. https://data.europa.eu/doi/10.2788/52966
• Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough?: An experiment with data saturation and variability. Field Methods, 18(1), 59–82. https://doi.org/10.1177/1525822X05279903
• Guillén-Gámez, F. D., & Mayorga-Fernández, M. J. (2020). Quantitative-comparative research on digital competence in students, graduates and professors of faculty education: An analysis with ANOVA. Education and Information Technologies, 25(5), 4157–4174. https://doi.org/10.1007/s10639-020-10160-0
• International Society for Technology in Education. (2024). ISTE Standards. ISTE. iste.org/standards
• Järvelä, S., Kirschner, P. A., Panadero, E., Malmberg, J., Phielix, C., Jaspers, J., Koivuniemi, M., & Järvenoja, H. (2015). Enhancing socially shared regulation in collaborative learning groups: Designing for CSCL regulation tools. Educational Technology Research and Development, 63(1), 125–142. https://doi.org/10.1007/s11423-014-9358-1
• Landis, J. R., & Koch, G. G. (1977). The Measurement of Observer Agreement for Categorical Data. Biometrics, 33(1), 159. https://doi.org/10.2307/2529310
• Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation (4th ed.). Jossey-Bass.
• Ottenbreit-Leftwich, A. T., Glazewski, K. D., Newby, T. J., & Ertmer, P. A. (2010). Teacher value beliefs associated with using technology: Addressing professional and student needs. Computers & education, 55(3), 1321-1335. https://doi.org/10.1016/j.compedu.2010.06.002
• Rummel, N., & Spada, H. (2005). Learning to collaborate: An instructional approach to promoting collaborative problem solving in computer-mediated settings. Journal of the Learning Sciences, 14(2), 201–241. https://doi.org/10.1207/s15327809jls1402_2
• Strauß, S., & Rummel, N. (2021). Promoting regulation of equal participation in online collaboration by combining a group awareness tool and adaptive prompts. But does it even matter? International Journal of Computer-Supported Collaborative Learning, 16(1), 67–104. https://doi.org/10.1007/s11412-021-09340-y
• Tondeur, J., Van Braak, J., Sang, G., Voogt, J., Fisser, P., & Ottenbreit-Leftwich, A. (2012). Preparing pre-service teachers to integrate technology in education: A synthesis of qualitative evidence. Computers & education, 59(1), 134-144. https://doi.org/10.1016/j.compedu.2011.10.009
• Utami, I. Q., Fahmiyah, I., Ningrum, R. A., Fakhruzzaman, M. N., Pratama, A. I., & Triangga, Y. M. (2022). Teacher’s acceptance toward cloud-based learning technology in Covid-19 pandemic era. Journal of Computers in Education, 9(4), 571–586. https://doi.org/10.1007/s40692-021-00214-8
• Venkatesh, Thong, & Xu. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157. https://doi.org/10.2307/41410412
• Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
• Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
• Venkatesh, V., Morris, Davis, & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540
• Vuorikari, R., Kluzer, S., & Punie, Y. (2022). DigComp 2.2: The Digital Competence Framework for Citizens. Publications Office of the European Union. https://doi.org/10.2760/115376
• Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge University Press.
• Yadegaridehkordi, E., Shuib, L., Nilashi, M., & Asadi, S. (2019). Decision to adopt online collaborative learning tools in higher education: A case of top Malaysian universities. Education and Information Technologies, 24(1), 79–102. https://doi.org/10.1007/s10639-018-9761-z
• Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.