Are Data Collection Tools for TPACK Suitable?
Serkan Dincer

Serkan Dincer, Cukurova University, Adana/Turkey. 

Manuscript received on 09 August 2019 | Revised Manuscript received on 16 August 2019 | Manuscript Published on 31 August 2019 | PP: 146-147 | Volume-8 Issue-9S2 August 2019 | Retrieval Number: I10290789S219/19©BEIESP DOI: 10.35940/ijitee.I1029.0789S219

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Despite a lot of studies existing in the literature about TPACK, it is still not obvious how to do TPACK measurement. However, when the studies investigating measurements are reviewed, it is seen that measurements are considered in informational aspect, and applications are held in only TK aspect or limited in TPC and TCK components. In this study, it is aimed to examine the differences and relationships between measurement instruments by focusing on TPACK measurements. Another goal of the study is to give an insight on how TPACK measurements should be realized. In the research, 213 teachers from different fields working in Turkey have participated and study is designed in Descriptive Survey Model. Three different tools were used in order to collect data. The results showed a meaningful relationship between individuals’ statements tools, but no meaningful relationship between individuals’ statements and performance tools. As a result of the study, many measurement instruments which measure participants’ TPACK measurements have been concluded that they do not actually measure TPACK. Apart from that, it has been found out that the teachers have difficulty in providing technology integration in education and the most important reason of this situation is that the teachers cannot manage to put technological knowledge content into practice.

Keywords: Data Collection, Technology Integration in Education, Technology Literacy, TPACK
Scope of the Article: Big Data Analytics for Social Networking using IoT