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    An ecological approach to technology appropriation: A sustainable digital learning material development ecosystem
    (IGI Global, 2020) Coskun, Tugra Karademir; Alper, Ayfer
    The study aims to construct an innovation-based digital learning material (DLM) development ecosystem that penetrates and sustains within the school culture in order to diffuse and maintain DLM development. Sixty-two teachers from 21 different branches participated in this nested mixed design study. Data were collected through scales and interviews, and the study was based on the steps adopted by Rogers on the diffusion of innovation. Quantitative data were analysed with cluster analysis, logistic and multi-linear regression. Qualitative data were analysed with structural, in vivo, and axial coding in order to construct the ecosystem. The findings demonstrate that the main variables, which were determined to influence the adoption and sustenance of DLM development by teachers, were the support of administrators and colleagues, the willingness and need to develop DLM, computer knowledge, and DLM development self-efficacy. © 2020 by IGI Global.
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    Evaluating the evaluators: A comparative study of AI and teacher assessments in Higher Education
    (Univ Barcelona, Res Group Educ & Virtual Learning, Digital Educ Observatory, 2024) Coskun, Tugra Karademir; Alper, Ayfer
    This study aims to examine the potential differences between teacher evaluations and artificial intelligence (AI) tool-based assessment systems in university examinations. The research has evaluated a wide spectrum of exams including numerical and verbal course exams, exams with different assessment styles (project, test exam, traditional exam), and both theoretical and practical course exams. These exams were selected using a criterion sampling method and were analyzed using BlandAltman Analysis and Intraclass Correlation Coefficient (ICC) analyses to assess how AI and teacher evaluations performed across a broad range. The research findings indicate that while there is a high level of proficiency between the total exam scores assessed by artificial intelligence and teacher evaluations; medium consistency was found in the evaluation of visually based exams, low consistency in video exams, high consistency in test exams, and low consistency in traditional exams. This research is crucial as it helps to identify specific areas where artificial intelligence can either complement or needs improvement in educational assessment, guiding the development of more accurate and fair evaluation tools.
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    The development and evaluation of self-directed digital learning material development platform for foreign language education*
    (Routledge Journals, Taylor & Francis Ltd, 2019) Karademir, Tugra; Alper, Ayfer; Soguksu, A. Fulya; Karababa, Z. Canan
    Foreign language education environments have become more colourful, interesting and effective with the use of digital learning materials over recent years. This research is aimed at developing a platform for designing self-guided digital learning materials to be used in teaching Turkish as a foreign language with an effort to promote the use of digital teaching materials in this field and to contribute to developing teachers' skills of designing digital materials. To this end, the Self-Directed Digital Learning Material Development Platform (SDLMD) was developed and evaluated by utilising the ADDIE model. The platform, which is free and open to all teachers and learners, is composed of five modules: puzzle, quiz, flashcard, matching and digital poster. The SDLMD is also incorporated with a storage system based on meta-data labels so that teachers can share their digital learning materials with learners and other teachers. The SDLMD was evaluated by 45 foreign language teachers through an online platform evaluation form including a rubric and open-ended questions. The results have revealed that the SDLMD is sufficient in terms of the eight evaluation themes, that it can serve as a valuable tool for both teachers and learners, and that it can contribute to improving teachers' skills of designing multimedia materials.
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    Usage of Digital Learning Material in Special Education
    (Ankara Univ, Fac Educational Sciences, 2019) Coskun, Tugra Karademir; Alper, Ayfer
    In this study, it is aimed to determine the opinions of special education teacher candidates regarding usage of digital learning materials in special education in their experience and reveal favorite digital learning materials platforms and reasons for preference. This study was designed with the phenomenological research method, and the participants of the research consisted of 49 freshman pre-service teachers of special education at a large university in the academic year of 2014-2015, Turkey. Research was continued for a total of 14 weeks: The first 6 weeks learning of digital learning material (DLM) tools, second 6 weeks learning augmented reality tool, 1 week developing materials and the last week interviewing with special education teacher candidates. Inductive content analysis was used in analyzing the data. Teacher candidates having their education at private institutions have stated that they wish to improve and use DLM. DLM is essential concerning increasing academic, social, self-care and communication skills. Additionally, teacher candidates have stated that DLMs support teachers with lower costs and time, student engagement, ease in preparation, fun and useful outcomes, and increase the variety and sources of materials. Participants have mentioned that unless the required technical equipment is provided, developing and using DLMs will not be possible.