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Collaborative Inquiry-based Learning

Authors: Suarez, Angel;

Collaborative Inquiry-based Learning

Abstract

This thesis presents the results of the conducted research and development of applications to support collaborative inquiry-based learning, with a special focus on leveraging learners’ agency. The reported results are structured into three parts: the theoretical foundations, the design and implementation and the evaluation. The first section contains chapter 1 that presents a literature review on how learners’ agency is supported in mobile inquiry-based learning processes. The classification was made in a two-step process. First, the most common mobile activities were extracted from the reviewed studies based on existing frameworks in mobile learning. The goal was to have a unique perspective on the studies that could reveal information on how the mobile technology was used for inquiry-based learning. The outcome of this first step was a list of 12 instructional designs organized into 5 main categories. The second step was to define a classification framework for learners’ agency that was based on existing definitions of agency and self-regulated learning. The result was a framework with six dimensions that characterize learners’ agency. The classification framework was used to evaluate to what extent the instructional designs supported learners’ agency. The findings helped designers and researchers to increase awareness and understanding about the role of mobile technology to exercise agency on inquiry-based learning. Section II –design and implementation– consisted of four chapters that presented an IBL infrastructure and two applications –the GPIM and DojoIBL– that built upon it. Chapter 2 explains one of the applications developed in this dissertation, the GPIM. It was a Google Glass® application meant to guide learners in data collection processes. Through the voice command and the HUD’s (Head-Up display) the users could experience hands-free operation, which made the differentiating element compared to other phone-based applications. This helped to improve the design requirements of the platform described in chapter 3, called the DojoIBL. DojoIBL is a cloud-based platform to structure and support collaborative inquiry-based learning processes, with an especial interest in leveraging learners’ agency. Its design focused on exposing a holistic view of the inquiry process to the learner, supporting learners’ agency through the use of roles, and structuring collaborative inquiry learning through the use of instant messaging, an inquiry timeline and notifications. However, analyzing learners’ agency in a collaborative online environment like DojoIBL, required more information about the traces that learners left behind in DojoIBL. Thus, in chapter 4, a new component called DojoAnalytics was presented to extend DojoIBL functionality with external Learning Analytics dashboards. The new component was designed following interoperability standards, in such a way that DojoAnalytics could channel the communication between DojoIBL and any standard LA dashboard. As a result, learners could monitor and self-regulate their progress based on actual performance using the external LA dashboards. To wrap up the section, chapter 5 presented the technical specification and documentation of a cloud-based IBL architecture built upon small, reusable components. This architecture consisted of the following six software components; 1) IBL engine, 2) authentication, 3) data collection, 4) communication, 5) notification and 6) DojoAnalytics, that provided means for researchers, designers, and developers to create new inquiry-based learning applications. Section III –evaluation– consisted of three chapters that present the evaluations carried out for the implementations. It began with chapter 6 presenting an empirical study that focuses on the impact of using different inquiry structures on perceived motivation, engagement, knowledge gain and cognitive load. This quasi-experimental study with 164 students compares three types of inquiry structure; one-phase structure, six-phase structure and six-phase structure with the support of a mobile app, the Personal Inquiry Manager. Findings show that the use of different structures for inquiry-based learning did not significantly influence the knowledge gain, motivation, and cognitive load. However, significant differences were found in the dependent variables influenced by the different educational cohorts and gender. The second evaluation, described in chapter 7, presented a formative study to assess DojoIBL users’ acceptance. To this end, the usability –using a System Usability Scale (SUS) questionnaire–, the users’ experience –using the User Experience Questionnaire (UEQ) – and a semi-structured interview with the students was used. The results show a high degree of users’ acceptance and the scores were within the 10% best results compared to a benchmark. Only dependability, which related to the perceived users’ control of the interaction, scored lower. This finding was aligned with students’ comments about usability issues, that later were addressed in a new iteration of DojoIBL. Finally, chapter 8 presented another study about DojoIBL that focused twofold on the optimal conditions to maximize the learning potential of DojoIBL and on leveraging learners’ agency through the use of roles. To this end, 10 students of the course of the ‘Language Learning and Acquisition’, carried out an inquiry about the listening and reading comprehension for 5 weeks. From the discourse analysis and the semi-structured interviews with the students, the findings of the study provided a list of practical guidelines that help to improve the management and support of collaborative inquiry processes through roles and DojoIBL.

Country
Netherlands
Related Organizations
Keywords

Doctoral Thesis, Learners' autonomy, Collaboration, Inquiry-based learning

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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
Average
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