Pre-Service Teachers' Online Teaching Readiness: Validation of Paliwal and Singh's Questionnaire

Sintia Triana, Herri Mulyono

Abstract


The present study aimed to investigate the psychometric characteristic of Paliwal and Singh's questionnaire used to evaluate pre-service teachers' readiness to teach online. Non-probability sampling was used to collect the required data from the participants. Using a suvery design, the study distributed Paliwal and Singh's (Paliwal & Singh, 2021) online questionnaire that was already translated into Indonesian. A total of 116 pre-service teachers took part in this study, but only eighty-eight responses from the participants were analysed due to data appropriateness. Rasch analysis was carried out to examine the unidimensionality aspect, person-item reliability, item statistics, person-item measure, and finally the item-person Wright map. The findings showed that nine-items of OTR developed by Paliwal and Singh questionnaire were valid to collect the data related to online teaching readiness. The Rasch analysis of Online Teaching Readiness revealed that the use of Rasch model to analyze this scale was suitable and produced a high level of reliability both for person and item. Findings of the study also suggest some implications and recommendations for future use of the questionnaire


Keywords


online teaching, online teaching readiness, pre-service teachers, Rasch analysis

Full Text:

PDF

References


Alston, S. T., Moore, C. S., & Thomas, M. (2017). Strategies for enhancing online teaching in social work education. Journal of Human Behavior in the Social Environment, 27(5), 412–423. https://doi.org/10.1080/10911359.2017.1311817

Boone, W. J., & Noltemeyer, A. (2017). Rasch analysis: A primer for school psychology researchers and practitioners. Cogent Education, 4(1). https://doi.org/10.1080/2331186X.2017.1416898

Caprara, G. V., Barbaranelli, C., Borgogni, L., Petitta, L., & Rubinacci, A. (2003). Teachers’, school staffs and parents’ efficacy beliefs as determinants of attitudes toward school. European Journal of Psychology of Education, 18(1), 15–31. https://doi.org/10.1007/BF03173601

Chan, M., & Subramaniam, R. (2020). Validation of a science concept inventory by Rasch analysis. In M. S. Khine (Ed.), Rasch Measurement: Applications in Quantitative Educational Research (Issue July, pp. 159–178). Springer Singapore. https://doi.org/10.1007/978-981-15-1800-3_9

Chan, S. W., Ismail, Z., & Sumintono, B. (2014). A rasch model analysis on secondary students’ statistical reasoning ability in descriptive statistics. Procedia - Social and Behavioral Sciences, 129, 133–139. https://doi.org/10.1016/j.sbspro.2014.03.658

Davis, N. L., Gough, M., & Taylor, L. L. (2019). Online teaching: advantages, obstacles and tools for getting it right. Journal of Teaching in Travel and Tourism, 19(3), 256–263. https://doi.org/10.1080/15313220.2019.1612313

Downing, J. J., & Dyment, J. E. (2013). Teacher educators’ readiness, preparation, and perceptions of preparing preservice teachers in a fully online environment: an exploratory study. Teacher Educator, 48(2), 96–109. https://doi.org/10.1080/08878730.2012.760023

Gay, G. H. E. (2016). An assessment of online instructor e-learning readiness before, during, and after course delivery. Journal of Computing in Higher Education, 28(2), 199–220. https://doi.org/10.1007/s12528-016-9115-z

Howard, S. K., Tondeur, J., Siddiq, F., & Scherer, R. (2021). Ready, set, go! Profiling teachers’ readiness for online teaching in secondary education. Technology, Pedagogy and Education, 30(1), 141–158. https://doi.org/10.1080/1475939X.2020.1839543

Huang, L., Huang, F., Oon, P. T., & Mak, M. C. K. (2019). Constructs evaluation of student attitudes towards science. Eurasia Journal of Mathematics, Science and Technology Education, 15(12). https://doi.org/10.29333/ejmste/109168

Hui, H., Jenatabadi, H., Ismail, N. A., & Radzi, C. W. J. W. M. (2013). Principal’s Leadership Style and Teacher Job Satisfaction: A Case Study in China. Interdisciplinary Journal of Contemporary Research In Business, 5(4), 175–184.

Hung, M. (2015). Teacher readiness for online learning: scale development and teacher perception. Computers & Education, 94, 120–133. https://doi.org/10.1016/j.compedu.2015.11.012

Lichoro, D. M. (2016). Faculty preparedness for transition to teaching online courses in the Iowa Community. 4(1), 1–23.

Ling Lee, W., Chinna, K., & Sumintono, B. (2020). Psychometrics assessment of HeartQoL questionnaire: A Rasch analysis. European Journal of Preventive Cardiology. https://doi.org/10.1177/2047487320902322

Liu, S., Xu, X., & Stronge, J. (2018). The influences of teachers’ perceptions of using student achievement data in evaluation and their self-efficacy on job satisfaction: evidence from China. Asia Pacific Education Review, 19(4), 493–509. https://doi.org/10.1007/s12564-018-9552-7

Martin, F., Budhrani, K., & Wang, C. (2019). Examining faculty perception of their readiness to teach online. Online Learning Journal, 23(3), 97–119. https://doi.org/10.24059/olj.v23i3.1555

Menon, M. E. (2014). The relationship between transformational leadership, perceived leader effectiveness and teachers’ job satisfaction. Journal of Educational Administration, 52(4), 509–528. https://doi.org/10.1108/JEA-01-2013-0014

Mulyono, H., Saskia, R., Arrummaiza, V. S., & Suryoputro, G. (2020). Psychometric assessment of an instrument evaluating the effects of affective variables on students’ WTC in face-to-face and digital environment. Cogent Psychology, 7(1), 1823617. https://doi.org/https://doi.org/10.1080/23311908.2020.1823617

Ningsih, S. K., Mulyono, H., Ar Rahmah, R., & Fitriani, N. A. (2021). A Rasch-based validation of EFL teachers’ received online social support scale. Cogent Education, 8(1), 1–13. https://doi.org/10.1080/2331186X.2021.1957529

Paliwal, M., & Singh, A. (2021). Teacher readiness for online teaching-learning during COVID − 19 outbreak: a study of Indian institutions of higher education. Interactive Technology and Smart Education, 18(3), 403–421. https://doi.org/10.1108/ITSE-07-2020-0118

Perrachione, B. A., Rosser, V. J., & Petersen, G. J. (2008). Why do they stay? elementary teachers’ perceptions of job satisfaction and retention. The Professional Educator, 32(2), 25–41.

Scherer, R., Howard, S. K., Tondeur, J., & Siddiq, F. (2021). Profiling teachers’ readiness for online teaching and learning in higher education: Who’s ready? Computers in Human Behavior, 118(December), 106675. https://doi.org/10.1016/j.chb.2020.106675

Skaalvik, E. M., & Skaalvik, S. (2014). Teacher self-efficacy and perceived autonomy: Relations with teacher engagement, job satisfaction, and emotional exhaustion. Psychological Reports, 114(1), 68–77. https://doi.org/10.2466/14.02.PR0.114k14w0

Wright, B. D. (1977). Solving measurement problems with the rasch model. Journal of Educational Measurement, 14(2), 97–116. https://doi.org/10.1111/j.1745-3984.1977.tb00031.x




DOI: https://doi.org/10.31004/edukatif.v4i3.2749

Article Metrics

Abstract view : 3 times
PDF - 3 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Sintia Triana, Herri Mulyono

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.