Session Information
27 SES 01 B, Promoting Student Engagment: Diversifying and Extending Learning Opportunities
Paper/Poster Session
Contribution
Introduction - Service-Learning
Service-Learning (S-L) defined by Europe Engage as “an innovative pedagogical approach that integrates meaningful community service or engagement into the curriculum and offers students academic credit for the learning that derives from active engagement within community and work on a real world problem. Reflection and experiential learning strategies underpin the learning process and the service is linked to the academic discipline”(Europe Engage), can be a high impact teaching and learning strategy in which academic learning and civic engagement are integrated to produce benefits for students, the community partner, the instructor and the higher education institution (see for instance Kuh, 2008; Seider, Gillmor & Rabinowicz, 2012). Other terms for S-L are community based learning, community engaged learning, civic learning, scholarship of engagement, learning-linked volunteering, etc. Latin-American countries and the United States have a long standing tradition in S-L (Mottart, 2017) and S-L is now increasingly emerging in Europe with Spain and Ireland as forerunners. In this respect, the Erasmus+ projects Europe Engage (2014-17) and EnRRICH (2015-17) were founded to specifically promote S-L. Europe Engage targeted at ‘developing a culture of civic engagement through S-L within higher education in Europe’; whereas the EnRRICH-project is more focused on responsible research to respond to the needs of societies.
Service-Learning in Belgian Higher Education Institutions.
Also in Belgium – the context of this study – higher education institutions are increasingly focusing on integrating S-L formally in their curriculum. The underlying dynamic is in many cases a combination of bottom-up (lecturer or student-driven) and top-down (board of the institution / head of departments) processes. For instance awarding credits to student’s extra-curricular engagement, or developing an institution-wide policy on the expertise and experiences of lecturers with S-L. Many lecturers are already familiar with aspects of S-L; e.g. through projects with societal partners, internships, intervision sessions with students, by collaborating with a science shop, by using real-life rather than text-book examples, etc. University lecturers have a large degree of freedom in the pedagogical approach of their teaching and thus they decide whether they incorporate S-L aspects in their course. The aim of this study is twofold: first to explore the differences between lecturers who do incorporate S-L (aspects) in their course and those who don’t; and second investigate how lecturers who don’t apply S-L (yet) can be motivated to incorporate S-L in their courses.
Service-Learning as an educational innovation / lecturer behavior
For this study we will draw on base social psychology models that were developed to explain and predict an individual’s behavior. Departing from the Theory of Reasoned Action (Fishbein & Ajzen, 1975), several models have been put forward which were in turn adapted to study different kinds of behavior, such as technology acceptance (e.g. Pynoo et al., 2011), the acceptance of an innovative approach (e.g. mobile commerce, Wu & Wang, 2005), volunteer enrollment by college students (Okun & Sloane, 2002), etc. In this study we use a combination of the Technology Acceptance Model (TAM; Davis, 1985) and the Theory of Planned Behavior (TPB; Ajzen, 1991) as theoretical framework to study university lecturers perceptions of S-L. Core variables in this model are perceived usefulness, perceived ease of use, attitude, subjective norms and perceived behavioral control as predictors of acceptance (operationalized by behavioral intention or a behavior) (Pynoo, et al., 2012).
This study will inform policy-makers of HEI on how to support and instigate HEI lecturers to incorporate S-L into their courses.
Method
This study was performed in the context of a larger baseline measurement on the current status of S-L and community-oriented initiatives at our institution, a university in Dutch-speaking part of Belgium. Sample Target population of this study was the teaching staff (professors, assistants, PhD’s). 253 faculty members started the study, of which 101 completed the survey. This sample was representative for job position and gender. The survey was open from November 23rd to December 31st 2018. The teaching staff was invited through email to fill out the survey and two follow-up emails were sent (after two and four weeks). Qualtrics was used for this study. Instrument The C-TAM-TPB was measured by Perceived Usefulness (PU, 2 items), Perceived Ease of Use (PEOU, 5 items), Attitude (ATT, 2 items), Subjective Norms (SN, 4 items), Perceived Behavioral Control (PBC, 6 items) and Behavioral Intention (BI, 4 items). Self-efficacy (4 items) was also included. The reliability (Cronbach Alpha) of all scales exceeded .80, except for Self-efficacy (.46). Means were computed for all scales except Self-efficacy. Other parts of the survey were amongst other demographic information, vision on S-L, partnerships, supportive measures, value of S-L, intracurricular S-L activities, and motives for not (yet) applying S-L.
Expected Outcomes
49 lecturers indicated that they had S-L experience in their teaching opposed to 77 without S-L experience. * Research aim 1: explore the differences between lecturers with and without S-L experience Preliminary analyses show that lecturers with S-L experience score significantly higher on all C-TAM-TPB scales compared to those without S-L experience. A logistic regression on S-L experience as a lecturer (Yes/No) with PU, PEOU, SN, ATT and PBC as covariates explains 40.7% of the variance (Nagelkerke Rsquare) in S-L experience, but only PEOU is a significant predictor. 77% of the cases could be classified correctly by the covariates, and especially the lecturers without experience (85.9%). * Research aim 2: investigate how lecturers without S-L experience can be motivated to incorporate S-L in their courses Linear regression showed that PU, ATT, SN and PBC explain 57% of the variance in BI in the group of lecturers with no S-L experience; and only ATT is not a significant predictor of BI. In our presentation at ECER we will focus on the broader picture and relate these results to the findings in the other parts of the survey to provide policy recommendations for promoting and supporting S-L at our university.
References
EnRRICH. https://www.livingknowledge.org/projects/enrrich/, URL accessed January 15, 2019. Europe engage. https://europeengage.org, URL accessed January 15, 2019. Kuh, G. (2008). High-Impact Educational Practices: What They Are, Who Has Access to Them, and Why They Matter. Association of American Colleges & Universities, 2008. Mottart, M. (2017). Handvaten voor een duurzame institutionele inbedding van service-learning in de Vlaamse hogeronderwijscontext. Tijdschrift voor Onderwijsrecht en onderwijsbeleid, 2017-18/3, 182-194. (in Dutch) Okun, M. A., & Sloane, E. S. (2002). Application of planned behavior theory to predicting volunteer enrollment by college students in a campus-based program. Social Behavior and Personality: an international journal, 30(3), 243-249. Pynoo, B., Devolder, P., Tondeur, J., Van Braak, J., Duyck, W., & Duyck, P. (2011a). Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study. Computers in Human Behavior, 27(1), 568-575. Pynoo, B., Tondeur, J., van Braak, J., Duyck, W., Sijnave, B. & Duyck, P. (2012). Teachers' acceptance and use of an educational portal. Computers & Education, 58(4), 1308-1317. Seider, S.C., Gillmor, S. & Rabinowicz, S. (2012). The Impact of Community Service Learning Upon the Expected Political Voice of Participating College Students. Journal of Adolescent Research, 27(1), 44-77 Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729.
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