Development and psychometric integrity of a measure in creative learning and innovative teaching

Giap Binh Nga 34 HNUE JOURNAL OF SCIENCE DOI: 10.18173/2354-1075.2017-0172 Educational Sciences, 2017, Vol. 62, Iss. 12, pp. 34-38 This paper is available online at DEVELOPMENT AND PSYCHOMETRIC INTEGRITY OF A MEASURE IN CREATIVE LEARNING AND INNOVATIVE TEACHING Giap Binh Nga Faculty of Psychology and Pedagogy, Hanoi National University of Education Abstract. Creativity is an important part of cognition but creativity assessments in learning and teaching are lacking. This paper describes the development of measures of Technology aspect, Innovative teaching, Creative learning and creative potential (TIC-c). Most items describe actual behaviors that clearly reflect an individual’s use of, appreciation of, and skill with creativity and innovation. Results obtained using both exploratory and confirmatory factor analysis is reported in this paper. These suggest the presence of 3 or 4 latent factors within the scale. Based on the theoretical underpinnings of the scale, a 4-factor solution was judged to be more interpretable than a 3-factor solution. Analyses also supported the mediated relationships among factors. Keywords: Creativity, creative learning, innovative teaching, creative potential. 1. Introduction Instrument development for creativity has become an essential to any organization that wish to sustain their competitive advantage in today’s world that has higher growth of new knowledge, ideas and accelerated rate of globalization [7]. The value that creativity and innovation offers lies in their ability to facilitate the development of novel and effective technological solutions to problems stimulated by change [3]. Therefore, Creativity and innovation are becoming increasingly important for the development of the 21 st century knowledge society. They contribute to economic prosperity as well as to social and individual wellbeing and are essential factors for a more competitive and dynamic nation [1]. Education is seen as central in fostering creative and innovative skills. It appears that opportunities to cultivate skills in creativity and innovation in higher education will soon become a necessity in order to meet these emerging demands [9]. At the present, creativity and innovation have been widely acknowledged as key skills for 21st century learning, yet it is unclear how best to develop them in higher education [5]. In the present study a newly developed instrument for university course evaluation in term of technology, innovative teaching, creative learning, and creative potential (TIC-c) is tested on a sample of participants of the courses of general psychology at the Hanoi National University of Education (N = 440). This TIC-c addressed both issues of creativity and innovation in learning and teaching consisted of 4 dimensions: technology, innovative teaching, creative learning, and creative potential. Aside from its prospective practical purposes, the TIC-c showed good psychometric properties, with regard to the internal consistency of subscales and overall factorial validity. We aim to develop an instrument of creativity assessment in learning and teaching and explore the relationships among creative learning, innovative teaching, and creative potential. Received: May 5, 2017. Revised: September 25, 2017. Accepted: October 19, 2017 Contact: Giap Binh Nga, e-mail address: giapbinhnga@yahoo.com Development and p sychometric integrity of a measure in creative learning and innovative teaching 35 2. Content 2.1. Sample Undergraduate students of General Psychology courses (N = 440), at the Hanoi National University of Education participated in this study. All of them are students who plan to become teachers at different levels of school in the northern of Vietnam. Participants included 78 males and 362 females with a range of age from 20 to over 25 years old. As for gender composition females were in majority (82%). Figure 1. Final confirmatory factor analysis of the TIC- c model 2.2. TIC-c development An instrument with closed-form items to assess student perception of Technology aspect (T), Innovative teaching (I), Creative learning (C) and creative potential (c) was developed. To assess different aspects of TIC-c, 63 statements were used. Responses were given on a 5-point Likert scale [4] for four subscales technology aspect, innovative teaching, creative learning, and creative potential dimensions. Some examples of items are as follow: Giap Binh Nga 36 - Item for technology aspect: I use the Internet to search for learning material. - Item for innovative teaching: The teacher uses equipments with high technologies. - Item for creative learning: I experiment the new ways of learning. - Item for creative potential: Creativity is a skill that can be applied to every school subject. For the 63 items, from item 1 to item 63, the response scale ranged from 1 "strongly disagree" to 5 "totally agree". The original goal was to create an instrument that contained 4 different factors of TIC-c, but initial analysis of pilot administration data suggested that the items were in fact too diverse. A priori item selection, which tightened the focus on the items that explicitly reflected TIC-c, produced a pool of 25 items. We used it to gather data in the sample and the data were analyzed by using SPSS software. Structural Equation Modeling (SEM) was used to evaluate the model appropriateness [6]. Both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are based on the common factor model [10]. The first model tested was a relatively simple model with 3 latent factors (Technology aspect, Education aspect, and Creative potential) with 25 measured variables. In the second model Education aspect factor was divided into 2 factors (innovative teaching and creative learning) as was suggested by EFA, thus comprising at the end of 4 factors. 2.3. Results After some adjustment made on the basis of theory and modification indices the better model was constructed. As for comparative fit indices, root mean square error of approximation (RMSEA) value is just at the border of good fit (.065). Standardized-Root-Mean-Residual (SRMR) = .060. In opposition, both comparative fit index (CFI) (.863) and Tucker-Lewis index (TLI) (.848) value fall short of being acceptable cut-off (Thompson, B., 2004). The instrument seems to have good practical value (see Figure 1). Mediating relationships The important point for mediating relationship is that a third variable plays an important role in governing the relationship between two other variables. Baron and Kenny (1986) argued that for us to claim a mediating relationship [2], we need to first show that there is a significant relationship in the direct pathway (see Figure 2) between the independent variable (innovative teaching) and the dependent variable (creative potential). Figure 2. The relationship between innovative teaching and creative potential, ** p < .01 The regression coefficient for the direct pathway innovative teaching on creative potential is 0.35. In this case, it is also correlation between innovative teaching and creative potential. Development and p sychometric integrity of a measure in creative learning and innovative teaching 37 The effect of Innovative teaching on Creative potential is partially mediated by Technology aspect (see Figure 3). The regression coefficient for the direct path innovative teaching on technology is 0.43, whereas the regression coefficient for the direct path technology on creative potential is 0.43. Then the regression coefficient for the indirect path innovative teaching on creative potential as product of single paths: 0.43 x 0.43 = 0.19. If innovative teaching changes by one standard deviation, then creative potential changes by 0.19 standard deviations via technology. The total path as product of sum up direct path and indirect path: 0.16 + 0.19 = 0.35. Figure 3. Partially mediated relationship The effect of Innovative teaching on Creative potential is fully mediated by Creative learning (see Figure 4). Figure 4. Fully mediated relationship The regression coefficient for the direct path innovative teaching on creative learning is 0.62, whereas the regression coefficient for the direct path creative learning on creative potential is 0.52. Then the regression coefficient for the indirect path innovative teaching on creative potential as product of single paths: 0.62 x 0.52 = 0.32. If innovative teaching changes by one standard deviation, then creative potential changes by 0.32 standard deviations via creative learning. The total path as product of sum up direct path and indirect path: 0.03 + 0.32 = 0.35. 3. Conclusion In this study, a new feedback form called TIC-c has been developed, the form that seems to be a Giap Binh Nga 38 valuable measure of creative learning and innovative teaching. The hypothesis that this instrument has adequate reliability and factorial validity as a measure of creative learning and innovative teaching was supported. 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