Abstract
The evaluation of teaching effectiveness is an important process of higher educational institutions. Having regulations, policies and procedures that guide the teaching activity strengthens the quality of teaching. There are several teaching effectiveness evaluation models that have been applied, each one with their own particularities, objectives and supporting tools. Furthermore, there are numerous studies about their validity, metrics, weighting, properties collection, among others. One of the main inputs for teaching evaluation is the student’s achievement, in addition to the qualitative assessment done by expert peers. With this baseline, we intend to design a new evaluation model capable of evaluating teaching quality. The model focuses on the instructor’s educational capacities that include innovative metrics that will allow the evaluation of his/her competences from a nonobjective perspective. To support the application of the model, we have designed an architecture where we integrate Semantic Technologies and Machine Learning algorithms for knowledge representation and information processing. As a result, we expect that the final system will be able to measure the effectiveness of the teaching activity of each professor and to identify potential problems in the applied teaching method.
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Acknowledgements
Work partially supported by the Autonomous Region of Madrid (grants “MOSI-AGIL-CM” (S2013/ICE-3019) co-funded by EU Structural Funds FSE and FEDER and Talent Attraction Program (“2017-T2/TIC-5664”)), project “SURF” (TIN2015-65515-C4-4-R (MINECO/FEDER)) funded by the Spanish Ministry of Economy and Competitiveness, and through the Excellence Research Group GES2ME (Ref. 30VCPIGI05) co-funded by URJC-Santander Bank.
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Orozco, W., Rodríguez-García, M.Á., Fernández, A. (2019). Teaching Effectiveness: An Innovative Evaluation Model. In: Uden, L., Liberona, D., Sanchez, G., Rodríguez-González, S. (eds) Learning Technology for Education Challenges. LTEC 2019. Communications in Computer and Information Science, vol 1011. Springer, Cham. https://doi.org/10.1007/978-3-030-20798-4_39
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