Browsing by Author "Hilleger, Isabel"

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A MOOC-based flipped experience: scaffolding SRL strategies improves learners’ time management and engagement
(2021) Pérez Sanagustín, María del Mar; Sapunar Opazo, Diego; Pérez Álvarez, Ronald Antonio; Hilleger, Isabel; Bey, Anis; Maldonado Mahauad, Jorge Javier; Baier, Jorge
Higher education institutions are increasingly considering the use of a form of blended learning, commonly named as flipped classroom (FC), in which students watch video lectures drawn from a massive online open course (MOOC) before a face-to-face lecture. This methodology is attractive, as it allows institutions to reuse high-quality material developed for MOOCs, while increasing learning flexibility and the students’ autonomy. However, the adoption of this methodology is low in general, especially in Engineering courses, as its implementation faces a number of challenges for students. The most salient challenge is the lack of student self-regulatory skills, which may result in frustration and low performance. In this paper, we study how a self-regulatory learning technological scaffold, which provides students with feedback about their activity in the MOOC, affects the engagement and performance of students in an Engineering course following a MOOC-based FC approach. To this end, we design an observational study with the participation of 242 students: 133 students in the experimental group (EG) who used a technological scaffold and 109 in the control group (CG) who did not. We did not find a statistically significant difference between the academic achievements of both groups. However, the EG exhibited a statistically significant greater engagement with the course and a more accurate strategic planning than the CG. The main implications for scaffolding self-regulated learning in FC derived from these results are discussed.
Can feedback based on predictive data improve learners' passing rates in MOOCs? a preliminary analysis
(Association for Computing Machinery, 2021) Pérez Sanagustín, María del Mar; Pérez Álvarez, Ronald Antonio; Maldonado Mahauad, Jorge Javier; Villalobos, Esteban; Hilleger, Isabel; Hernández Correa, Josefina; Sapunar, Diego; Moreno Marcos, Pedro Manuel; Muñoz Merino, Pedro; Delgado Kloos, Carlos; Imaz, Jon
This work in progress paper investigates if timely feedback increases learners’ passing rate in a MOOC. An experiment conducted with 2,421 learners in the Coursera platform tests if weekly messages sent to groups of learners with the same probability of dropping out the course can improve retention. These messages can contain information about: (1) the average time spent in the course, or (2) the average time per learning session, or (3) the exercises performed, or (4) the video-lectures completed. Preliminary results show that the completion rate increased 12% with the intervention compared with data from 1,445 learners that participated in the same course in a previous session without the intervention. We discuss the limitations of these preliminary results and the future research derived from them.
Identifying needs for learning analytics adoption in Latin American universities: a mixed-methods approach
(2020) Hilleger, Isabel; Ortiz Rojas, Margarita Elizabeth; Pesantez Cabrera, Paola Karina; Scheihing, Eliana; Tsai, Yi Shan; Muñoz Merino, Pedro; Broos, Tom; Whitelock Wainwright, Alexander; Pérez Sanagustín, Mar
Learning Analytics (LA) is perceived to be a promising strategy to tackle persisting educational challenges in Latin America, such as quality disparities and high dropout rates. However, Latin American universities have fallen behind in LA adoption compared to institutions in other regions. To understand stakeholders' needs for LA services, this study used mixed methods to collect data in four Latin American Universities. Qualitative data was obtained from 37 interviews with managers and 16 focus groups with 51 teaching staff and 45 students, whereas quantitative data was obtained from surveys answered by 1884 students and 368 teaching staff. According to the triangulation of both types of evidence, we found that (1) students need quality feedback and timely support, (2) teaching staff need timely alerts and meaningful performance evaluations, and (3) managers need quality information to implement support interventions. Thus, LA offers an opportunity to integrate data-driven decision-making in existing tasks. © 2020 Elsevier Inc.