Computer-supported Inquiry Learning Research Articles

Comment on Zacharia et al., A review of data about effectiveness of guidance in computer supported, inquiry based learning laboratories and simulations

This review is in response to “Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: a literature review,” by Zacharia et al. (Educ Technol Res Dev 63:257–302, 2015). This review is focused on the perspective of a high school teacher or college professor attempting to provide a computer supported inquiry learning (CoSIL) environment for use online or in a classroom. The impact of Zacharia et al. is strong, as it is an excellent summary of (1) the optimal phases of inquiry based learning (IBL) experience and (2) the categories of guidance that that are effective at fostering student progress through IBL experiences. Application of this paper is as a Rosetta Stone to allow teachers, game designers and education researchers to communicate and build in the same space to create a blended experience. The limitation of this paper is that there are not yet very many studies of guidance and its effect on computer assisted IBL. Future suggestions are for teachers to use computer based simulations, add discussion and simple, real life activities to provide optimal IBL experience. Teachers can add their own guidance to support computer based simulations thus providing an enhanced experience for shifting to digital.

Advancing automatic guidance in virtual science inquiry: from ease of use to personalization.

This article is in response to the review entitled “Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: a literature review” (Zacharia et al. in Educ Technol Res Dev 63(2): 257–302). As COVID-19 alerts us to shift science education to digital when in-person schooling is not viable, one approach to facilitate this shift, as reviewed by Zacharia et al. (2015), is to involve students in computer supported inquiry learning (CoSIL) with appropriate guidance. As CoSIL guidance is critical to student success in CoSIL, Zacharia et al. (2015) contribute to our knowledge by systematically reviewing the forms and the efficacy of such guidance tools that are associated with each phase of scientific inquiry. With such knowledge we may develop decent guidance so that students can experience scientific inquiry virtually as they used to do in-person. Zacharia et al. (2015) indicated that the various guidance tools had increased the ease of use of CoSIL but failed in personalizing CoSIL to individual students. I agree with Zacharia et al. that the personalization of CoSIL guidance is vital. Further, I argue that the emergent machine learning may significantly increase the personalization of CoSIL without burdening teachers. I conclude the essay with suggestions to further investigate the cognitive needs of students in CoSIL and integrate the content, CoSIL, and guidance tools, as a way to move forward the personalization of CoSIL.

Insights on identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science.

This paper is in response to the literature review entitled “Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: a literature review” [Zacharia et al., Educational Technology Research and Development, 63, 257–302 (2015). 10.1007/s11423-015-9370-0] and examines it from a value-add perspective. This literature review illuminates the benefits of leveraging the appropriate types of guidance during the relevant phases of inquiry, a much-needed type of guidance, as it aptly describes how and when to apply the types of guidance for optimal effect. In consideration of some of the weaknesses in the body of literature, as exposed via this literature review, revisiting automated guidance and leveraging any new technological affordances and awareness around adaptive feedback may provide additional insights into how more advanced technologies might contribute to enhanced guidance in computer supported inquiry learning environments.

A primer for transitioning to online science labs: “Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science”

This paper is in response to the manuscript entitled “Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: a literature review” (Zacharia et al., Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: A literature review. Educational Technology Research and Development, 63(2), 257–302, 2015) from a design perspective. The review article identified specific types of guidance to support all forms of inquiry in online labs within the computer supported inquiry learning (CoSIL) environments. During the sudden shift to digital educators and students faced challenges due to lack of preparation to cultivate skills for teaching and learning in the online format. Educators developing and delivering instructions require a range of tools to operationalize the inquiry process in online science labs. Application of the tools provided in this review will support educators venturing into designing online science labs for engaging learners in scientific inquiry. This review have immense impact on how instructors can provide guidance to support learners’ inquiry in online science labs. The limitations include further investigation and modification of several tools that the review provided for implementation in future. Further research is needed to design and facilitate model CoSIL environment for online science labs to support and sustain the process of inquiry learning. This review has significant implication in providing comprehensive information amidst traversing crisis in context to shifting to online labs for supporting inquiry phases as documented in the CoSIL research.

Ideas for supporting student-centered stem learning through remote labs: a response.

This paper is in response to the article entitled “Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: a literature review” by Zacharia et al. (2015). In their review, Zacharia et al. (2015) adopted de Jong and Lazondo’s (2014) framework of five inquiry phases for online labs: orientation, conceptualization, investigation, conclusion, and discussion. Zacharia et al. reviewed the literature on Computer-supported Inquiry Learning (CoSIL), and identified best practices for each phase. They concluded, for example, that the orientation/conclusion/discussion phases received the least amount of guidance, while there were many more tools and strategies for providing guidance in the conceptualization/investigation phases. In this paper, we adopt the same inquiry framework as Zacharia et al. (2015) and report strategies that we learned from STEM faculty about how they supported and guided virtual student lab-based learning in these five phases during the recent COVID-19 shutdown. While Zacharia et al. identified tools and processes for enabling all five inquiry phases, add additional practical examples of faculty implementing these phases online as part of COVID-19 emergency remote teaching, and we provide insights for extending the 5-phase framework for future research.

How Much Guidance Students Need When Designing Experiments in a Computer-Supported Inquiry Learning Environment

How Much Guidance Students Need When Designing Experiments in a Computer-Supported Inquiry Learning Environment

Collaborative group engagement in a computer-supported inquiry learning environment

Computer-supported collaborative learning environments provide opportunities for students to collaborate in inquiry-based practices to solve authentic problems, using technological tools as a resource. However, we have limited understanding of the quality of engagement fostered in these contexts, in part due to the narrowness of engagement measures. To help judge the quality of engagement, we extend existing engagement frameworks, which have studied this construct as a stable and decontextualized individual difference. We conceptualize engagement as multi-faceted (including behavioral, social, cognitive and conceptual-to-consequential forms), dynamic, contextualized and collective. Using our newly developed observational measure, we examine the variation of engagement quality for ten groups. Subsequently, we differentiate low and high quality collaborative engagement through a close qualitative analysis of two groups. Here, we explore the interrelationships among engagement facets and how these relations unfolded over the course of group activity during a lesson. Our results suggest that the quality of behavioral and social engagement differentiated groups demonstrating low quality engagement, but cognitive and conceptual-to-consequential forms are required for explaining high quality engagement. Examination of interrelations indicate that behavioral and social engagement fostered high quality cognitive engagement, which then facilitated consequential engagement. Here, engagement is evidenced as highly interrelated and mutually influencing interactions among all four engagement facets. These findings indicate the benefits of studying engagement as a multi-faceted phenomenon and extending existing conceptions to include consequential engagement, with implications for designing technologies that scaffold high quality cognitive and conceptual-to-consequential engagement in a computer-supported collaborative learning environment.

Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: a literature review

The aim of this review is to identify specific types of guidance for supporting student use of online labs, that is, virtual and remote labs, in an inquiry context. To do so, we reviewed the literature on providing guidance within computer supported inquiry learning (CoSIL) environments in science education and classified all identified guidance according to a recent taxonomy of types of guidance. In addition, we classified the types of guidance in phases of inquiry. Moreover, we examined whether the types of guidance identified for each inquiry phase were found to be effective in promoting student learning, as documented in the CoSIL research. This review identifies what types of effective guidance currently exist and can be applied in developing future CoSIL environments, especially CoSIL environments with online labs. It also highlights the needs/shortcomings of these available types of guidance. Such information is crucial for the design and development of future CoSIL environments with online labs.

THE ROLE OF GENERAL INQUIRY KNOWLEDGE IN ENHANCING STUDENTS’ TRANSFORMATIVE INQUIRY PROCESSES IN A WEB-BASED LEARNING ENVIRONMENT

Inquiry has been regarded internationally as an effective learning approach for science learning; however, it is still not actively used in many schools. The current study argues that one of the reasons is incompleteness of the model for inquiry. This study seeks to open inquiry from a new angle by bringing in general inquiry knowledge, which could be regarded as an important limitation in enhancing inquiry. Next, it is empirically tested if general inquiry knowledge is related to the level of students’ transformative inquiry skills. General inquiry knowledge pertains to the nature of a coherent inquiry process as a whole, comprehending knowledge about transformative and regulative inquiry processes. In this study, students’ general inquiry knowledge and transformative inquiry skills were evaluated in a web-based learning environment Young Researcher. The analysis of the results demonstrated that the learning environment was suitable for improving students’ general inquiry knowledge, and these are related with the level of transformative inquiry skills. Key words: computer-supported inquiry learning, general inquiry knowledge, inquiry learning, inquiry meta-processes, transformative and regulative inquiry processes.

Investigating student engagement in computer-supported inquiry: a process-oriented analysis

The aim of this article is to describe and analyze how computer supported inquiry learning effects two secondary school students’ engagement in a literacy learning project. With comparative analysis of various sources of data we aim to understand what engagement is, how and why it changes over time and how changes in engagement are reflected in what learners do in an actual learning context. A set of methods was implemented that aimed at process-oriented analyses in a natural context of learning, that is, observations, interviews, content analysis of computer notes and an experience sampling questionnaire. The results show that even though the students had very different motivational tendencies in a traditional classroom, both of them showed progressive task engagement in this learning project. The data also illustrate how a technology supported environment can influence the way the students construct their goals and structure their activity. We conclude that multidimensional concepts, like engagement, have the potential to link the antecedents and consequences of how students behave, how they feel, and how they think, especially in the context of new pedagogical and technology-based learning environments.

Issues in computer supported inquiry learning in science

Journal of Computer Assisted LearningVolume 23, Issue 2 p. 111-119 Issues in computer supported inquiry learning in science W.R. Van Joolingen, Corresponding Author W.R. Van Joolingen Faculty of Behavioral Sciences, University of Twente, Enschede, the NetherlandsWouter R. van Joolingen, Faculty of Behavioral Sciences, University of Twente, PO Box 217, 7500 AE Enschede, the Netherlands. Email: W.R.vanJoolingen@utwente.nlSearch for more papers by this authorT. De Jong, T. De Jong Faculty of Behavioral Sciences, University of Twente, Enschede, the NetherlandsSearch for more papers by this authorA. Dimitrakopoulou, A. Dimitrakopoulou University of the Aegean, Rhodes, GreeceSearch for more papers by this author W.R. Van Joolingen, Corresponding Author W.R. Van Joolingen Faculty of Behavioral Sciences, University of Twente, Enschede, the NetherlandsWouter R. van Joolingen, Faculty of Behavioral Sciences, University of Twente, PO Box 217, 7500 AE Enschede, the Netherlands. Email: W.R.vanJoolingen@utwente.nlSearch for more papers by this authorT. De Jong, T. De Jong Faculty of Behavioral Sciences, University of Twente, Enschede, the NetherlandsSearch for more papers by this authorA. Dimitrakopoulou, A. Dimitrakopoulou University of the Aegean, Rhodes, GreeceSearch for more papers by this author First published: 12 January 2007 https://doi.org/10.1111/j.1365-2729.2006.00216.xCitations: 111Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume23, Issue2April 2007Pages 111-119 RelatedInformation

Computer-supported inquiry learning: effects of training and practice

Inquiry learning requires the ability to understand that theory and evidence have to be distinguished and co-ordinated. Moreover, learners have to be able to control two or more independent variables when formulating hypotheses, designing experiments and interpreting outcomes. Can sixth-grade (9–10 years) children be trained to acquire these inquiry learning skills? Or is the opportunity to practice in a computer-supported simulation environment a sufficient condition to foster inquiry learning skills? In this study, two groups of sixth grade children were compared: a training group, and a practice group. The training group received an off-line inquiry learning training in which we focused on fostering strategies for proper inferencing and designing experiments. The practice group conducted four inquiry learning tasks during two practice sessions. Learning outcomes and inquiry learning process measures were collected to study whether training and practice resulted in desired changes in learning behaviour. Both training and practice resulted in better performance during the test problems. Compared to the practice group, the training group showed some advantage in discovering an interaction effect. Practice and training effects appeared to be dependent on type of domain.