ECLECTIC as a learning ecosystem for higher education disruption

Abstract

The learning teaching paradigm in higher education is currently undergoing great transformation due to the irrefutable imposition, on the one hand, of the new technologies and, on the other, by the characteristics (habits and abilities) presented by the students that arrive to universities. These factors are not compatible with the teaching methodologies commonly used to date, that is, with the traditional model (lectures) consolidated in the nineteenth century. In this context, teachers who resort to active learning have attracted a lot of attention, since this type of approach stimulates students' motivation and autonomy to acquire more competencies and is one of the guidelines of the European Norms and Guidelines for Quality in Higher Education. Thus, as a way of responding to these challenges, an innovative pilot project was developed, from the pedagogical point of view, implemented in a first cycle course (Management and Information Systems) using active methodologies. In this framework, an approach called ECLECTIC was developed and implemented with the use of three active learning techniques (group project, peer review and peer teaching) in the "New Trends in IT" course, from first semester, second year. The results obtained are very promising, since they have allowed students to engage in and out of the classroom and have resulted in a high-rate course success.

Task-based Autoethnographic Pedagogical Approach: a phenomenological inquiry into online learning of Critical Food Studies courses

“…Task-based autoethnography as a pedagogical approach has evolved considering the ethos of the Critical Food Studies curriculum. Grounded within the principles of active learning (Freeman et al, 2014 ; Moreira et al, 2019 ) and aligning with the intersecting goals of critical autoethnography (Holman Jones, 2019 ), TAPA provides the possibility for the learners to critically engage and curate knowledge on food and its intersections with their own everyday lives. The tasks provide the learners with first-hand exposure and experience to the practices of sourcing, cooking, eating, and reflecting on food production, consumption, and food waste management.…”

“…These designs have been an integral part of teaching–learning engagement since the latter half of the twentieth century when the paradigm shift from teacher-centric pedagogical designs began (Cornelius-White, 2007 ). Additionally, as online learning emerged as a viable alternative mode of instruction at the beginning of the twenty-first century, learner-centric and praxis-based pedagogical designs that incorporated active learning principles gained popularity because they supported student achievement and motivation, which in turn led to deeper learning (Moreira et al, 2019 ; Phillips, 2005 ). Strategic and design guidelines that enabled and enhanced learner participation, personalized feedback, and peer and self-assessment, thereby facilitating learner-centered communities can be identified widely in literature on online learning (Yousef et al, 2014 ).…”

New methods and technologies for enhancing usability and accessibility of educational data

“…There are many types of data that can support student’s learning [ 31 ], but the type and nature of the data, how they can be accessed, and who can access them, vary significantly. Whether educational data are collected from collaborative learning environments [ 32 – 34 ], course management systems [ 35 , 36 ], gamified training applications [ 37 , 38 ], or administrative systems from schools and universities [ 39 – 41 ], valuable properties, patterns, and insights often emerge. When combined with other factors such as timing and context, these factors play an important role in understanding how students learn [ 42 ], the settings in which they learn [ 43 ], and the effectiveness of the educational approaches [ 44 ].…”

New methods and technologies for enhancing usability and accessibility of educational data

“…There are many types of data that can support student’s learning [ 31 ], but the type and nature of the data, how they can be accessed, and who can access them, vary significantly. Whether educational data is collected from collaborative learning environments [ 32 – 34 ], course management systems [ 35 , 36 ], gamified training applications [ 37 , 38 ], or administrative systems from schools and universities [ 39 – 41 ], valuable properties, patterns, and insights often emerge. When combined with others factors such as timing and context, these factors play an important role in understanding how students learn [ 42 ], the settings in which they learn [ 43 ], and the effectiveness of the educational approaches [ 44 ].…”