Antonio Calderon – @acalderon_pe
Lourdes Merono – @Lourdes_Mer_Gar
UCAM Catholic University of Murcia (Spain)
Students, in general, show positive attitudes and beliefs about social media uses in education (Mao, 2014). A majority of them appear to enjoy online social networking use, resulting in the creation of a more interactive and appealing learning environment, hence, increasing their learning motivation (Lu & Churchill, 2014). Nevertheless, in the social networking environment students appeared to enhance social engagement, but a high level of cognitive engagement was not demonstrated (Lu & Churchill, 2014).
This paper analyses the effect of a student-centred social media intervention on intrinsic motivation and motivational climate of first year undergraduate degree students. The student-centred social media intervention was composed by the ‘socio-digital technology-based tasks’ (mini-challenges).
Every mini-challenge included six steps to be completed. All the students, within an assessment for learning process, had to: (1) search information from the internet about the main mini-challenge question (to guide the search it is recommended different blogs, journal articles, twitter accounts, etc., through an attractive mini-challenge info presentation); (2) curate and sort the information (gathering just the relevant information, sense-making); (3) design an infography (using specific software, i.e. Piktochart, PowToon and Genially) that addresses the main mini-challenge question; (4) share the infography through social media sites (Twitter) mentioning and trying to interact with at least one of the authors or websites in which the information to create the infography has been taken; (5) self-assess the piece through a one to five points rubric, and lastly (6) post a reflection about the whole process on their learning blogs and tweet it out the mini-challenge ‘learning tweet’, always using the hashtag of the course (#FIDmola).
Two intact classes (n=110) and one lecturer participated. Eight mini-challenges were completed along the semester. This paper followed a mixed-methods approach. The quantitative data was collected after having completed all the mini-challenges through the Task Evaluation Questionnaire (TEQ) (Ryan, Koestner, & Deci, 1991) and the Learning Climate Questionnarie (LCQ) (Williams, & Deci, 1996). The TEQ is a 22 item questionnaire that has been used in some studies on intrinsic motivation. It has four subscales: interest/enjoyment, perceived choice, perceived competence, and pressure/tension.
The LCQ is a 15 item questionnaire that is typically used with respect to specific learning settings, such as a particular class, at the college or graduate school level. The qualitative data about students’ perception of intrinsic motivation and motivational climate were collected from students’ tweets and the students’ blogs and coded using QSR NVivo 11 software. For data analysis, first, the descriptive statistics (means and standard deviations), the internal consistency, and the bivariate correlations of the different dependent variables study (learning climate and intrinsic motivation) were calculated using IBM SPSS v22. Second, a measurement model and a structural equation model were designed to analyze the hypothesized relationships among the dimensions ‘interest/enjoyment’, ‘perceived competence’, ‘perceived choice’ and ‘pressure/tension’ using the statistical program AMOS18.
The results showed correct psychometric quality, internal consistency, reliability and the adequacy of the structural model: χ2/df = 1.71, TLI = 0.91, CFI = 0.95, GFI = 0.95, RMSEA = 0.04, y SRMR = 0.08. The mini-challenges’ pedagogy improved their interest and the enjoyment of the students. This increases their perceived competence and reduces their pressure-tension towards the final assessment and grading. As some students noted: ‘thanks to the mini-challenges I’ve been fully motivated in the course content’; or ‘this is a new and innovative way to learn that I really like’; or ‘I’d love more and more courses use this pedagogy’. After the intervention the intrinsic motivation of the undergraduate students was high. As a consequence the class motivational climate determined optimal levels of engagement and learning of the first year undergraduate degree students.
References:
Lu, J., & Churchill, D. (2014). The effect of social interaction on learning engagement in a social networking environment. Interactive learning environments, 22(4), 401-417. doi: 10.1080/10494820.2012.680966
Mao, J. (2014). Social media for learning: A mixed methods study on high school students’ technology affordances and perspectives. Computers in Human Behavior, 33, 213-223. doi: 10.1016/j.chb.2014.01.002
Ryan, R. M., Koestner, R., & Deci, E. L. (1991). Varied forms of persistence: When free-choice behavior is not intrinsically motivated. Motivation and Emotion, 15, 185-205.
Teo, T. (2015). Comparing pre-service and in-service teachers’ acceptance of technology: Assessment of measurement invariance and latent mean differences. Computers & Education, 83, 22-31. doi:10.1016/j.compedu.2014.11.015
Williams, G. C., & Deci, E. L. (1996). Internalization of biopsychosocial values by medical students: A test of self-determination theory. Journal of Personality and Social Psychology, 70, 767-779.