Antonio Calderon – @acalderon_pe
Lourdes Merono – @Lourdes_Mer_Gar
UCAM Catholic University of Murcia (Spain)
Despite controversy regarding the value of the educational role of social media, recent empirical studies suggest that digital technology could improve teaching and learning experiences in higher education (Balakrishnan, 2014). Nevertheless, students’ perception about the usefulness of social media in an academic context varies widely (Klein, 2008). Many acknowledge the ability to access academic information quickly, the convenience of direct communication, the improvement of critical thinking skills and a perception of their academic achievement. Nevertheless, some students perceive social media as distracting, time-consuming, and made for leisure and socializing activities rather than academic purposes.
This paper explores the perception of first year undergraduate degree students about their learning after experiencing a semester course with 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. The workflow analysis protocol utilized both qualitative and quantitative data collection methods (mixed-methods).
The qualitative data about students’ perception were collected from students’ tweets and students’ learning blogs and were coded using QSR NVivo 11 software. The quantitative data was collected after to have completed all the mini-challenges through the Perceived Competence for Learning (Williams, Freedman, & Deci, 1998) and the Intrinsic Motivation Inventory (short version of McAuley, Duncan, and Tammen, 1987). For data analysis, first the descriptive statistics (means and standard deviations), the internal consistency, and the bivariate correlations of the different dependent variables study (perceived learning 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 ‘perceived competence for learning’, ‘effort/importance’ and ‘value/usefulness’ using the statistical program AMOS18.
After the analysis it was found that the first year undergraduate degree students had a very positive perception about the mini-challenges and a high perception of competence for learning. The mini-challenges’ pedagogy improved their autonomy and their ability to create and share contents what is essential for a meaningful and sustainable teaching and learning (Fletcher, 2016). As some students noted: ‘this way is easier to learn and be engaged with the content’; or ‘I really like to share my infographies on Twitter and connect with others students and scholars’; or ‘at first, I spent a lot of time using this new software, but now I feel mucho more competence and I’m using it to create my personal stuff’. Furthermore, the results showed correct psychometric quality, internal consistency, reliability and the adequacy of the structural model: χ2/df = 2.72, TLI = 0.84, CFI = 0.95, GFI = 0.95, RMSEA = 0.06, y SRMR = 0.08. The use of mini-challenges as a part of the teaching process in higher education with first year undergraduate students provokes an optimal level of engagement and learning that led to an authentic learning experience.
References:
Balakrishnan, V. (2014). Using social networks to enhance teaching and learning experiences in higher learning institutions. Innovations in Education and Teaching International, 51(6), 595-606.
Fletcher, T. (2016). Developing principles of physical education teacher education practice through self-study. Physical Education and Sport Pedagogy, 21(4), 347-365. doi: 10.1080/17408989.2014.990370
Klein, J. (2008). Social networking for the K-12 set. Learning & Leading with Technology, 12(5), 1-5.
McAuley, E., Duncan, T., & Tammen, V. V. (1987). Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: A confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60, 48-58.
Williams, G. C., Freedman, Z. R., & Deci, E. L. (1998). Supporting autonomy to motivate glucose control in patients with diabetes. Diabetes Care, 21, 1644-1651.