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Can connectivism explain how students learn?

Pode o conectivismo explicar como os alunos aprendem?
Authors: AlDahdouh, Alaa Ahmad Mustafa;

Can connectivism explain how students learn?

Abstract

This thesis seeks to map and understand the cognitive, social, emotional and motivational aspects involved in the problem-solving processes of the new generation of higher education students while resolving their academic tasks. Adopting a new learning theory called Connectivism – that assumes knowledge structure as a network and learning as a process of finding patterns residing in this network – as the main conceptual framework, the thesis seeks to investigate the applicability of Connectivism’s principles to explain these processes. Starting with a pilot study (with two Portuguese students) to test the feasibility of a specific research method – retroverted think aloud – the empirical part of the study involved, in the main study, a group of nine Palestinian students from Gaza universities. Each of them completed a set of 10 tasks and all the steps of this process were monitored and evaluated by means of recording video of their searching internet activities; writing diary on paper material; copying and pasting online conversations with their friends, teachers, and relatives; and responding to Media and Technology Usage and Attitudes Scale (MTUAS Rosen, Whaling, Carrier, Cheever, & Rokkum, 2013), and the Post- Experiment Questionnaire, an instrument specifically designed for this experiment. The results of the study suggested that Connectivism theory provides a valuable framework for interpreting how the Net Generation of higher education students learn, but it still needs some refinements. For example, Connectivism’s principles didn’t mention clearly the evaluation process of the nodes in the knowledge network as a distinctive and needed skill for learning. According to the results of this thesis, planning, forethought, or decision-making process was not enough to guide students’ learning. The failure in the planning process might lead learners to visit unrelated nodes, but the failure in the evaluation process would make the learners delve into them. In addition, connectivists contended that they aim to help learners creating their own Personal Learning Network (PLN) but the results indicated that the learners are busy and driven by academic tasks and they are not aware of this kind of learning. The first step, as the results suggested, would be to allow students to know about PLN and then help them in building it. Moreover, the principle of Connectivism indicating that the newness is the intent of all connectivist learning activities didn’t reflect the diversity of the participants’ goals. The thesis suggested refining the principle to include other goals such as self-oriented, task-oriented, teacher-oriented, and others-oriented goals. Finally, connectivists assumed that negative emotions encourage students to make new connections. Although the thesis supported this assumption to a certain degree, this did not always hold true. Negative-activating emotions sometimes developed into negative-deactivating emotions which, in turn, developed to failure in the task.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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