Tools for Science Inquiry Learning: Tool Affordances, Experimentation Strategies, and Conceptual Understanding

Bumbacher, Engin; Salehi, Shima; Wieman, Carl; Blikstein, Paulo

doi:10.1007/s10956-017-9719-8

Cited by 46 publications

(41 citation statements)

References 62 publications

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“…To do so, a temporary blocking of the PROG phase (i.e., blocking the access to the programming interface) is proposed as an instructional intervention. Based on the findings of similar approaches implemented for inquiry-based learning (Bumbacher et al, 2018;Dillenbourg, 2013;Perez et al, 2017), the main idea is to introduce strategic pauses to the students to reinforce the three phases preceding the PROG phase. However, creating one loop to replace another is not a sustainable solution.…”

Section: Research Questionmentioning

confidence: 99%

“…In many different learning situations, however, researchers have shown that a pure trial-and-error-approach may limit skill development (Antle, 2013;Sadik, Leftwich, & Nadiruzzaman, 2017;Tsai, Hsu, & Tsai, 2012). In the context of inquiry-based science learning, Bumbacher et al have shown that students who were instructed to follow a Predict-Observe-Explain (POE) strategy, forcing them to take breaks between actions, gained better conceptual understanding than students who used the same manipulative environment without any instructions (Bumbacher, Salehi, Wieman, & Blikstein, 2018). The strategic use of pauses has also been investigated by Perez et al (2017) in the context of students who worked with a virtual lab representing a DC circuit construction kit.…”

Section: Introductionmentioning

confidence: 99%

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Fostering computational thinking through educational robotics: a model for creative computational problem solving

et al. 2020

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Background: Educational robotics (ER) is increasingly used in classrooms to implement activities aimed at fostering the development of students' computational thinking (CT) skills. Though previous works have proposed different models and frameworks to describe the underlying concepts of CT, very few have discussed how ER activities should be implemented in classrooms to effectively foster CT skill development. Particularly, there is a lack of operational frameworks, supporting teachers in the design, implementation, and assessment of ER activities aimed at CT skill development. The current study therefore presents a model that allows teachers to identify relevant CT concepts for different phases of ER activities and aims at helping them to appropriately plan instructional interventions. As an experimental validation, the proposed model was used to design and analyze an ER activity aimed at overcoming a problem that is often observed in classrooms: the trial-and-error loop, i.e., an overinvestment in programming with respect to other tasks related to problem-solving. Results: Two groups of primary school students participated in an ER activity using the educational robot Thymio. While one group completed the task without any imposed constraints, the other was subjected to an instructional intervention developed based on the proposed model. The results suggest that (i) a non-instructional approach for educational robotics activities (i.e., unlimited access to the programming interface) promotes a trial-and-error behavior; (ii) a scheduled blocking of the programming interface fosters cognitive processes related to problem understanding, idea generation, and solution formulation; (iii) progressively adjusting the blocking of the programming interface can help students in building a well-settled strategy to approach educational robotics problems and may represent an effective way to provide scaffolding. Conclusions: The findings of this study provide initial evidence on the need for specific instructional interventions on ER activities, illustrating how teachers could use the proposed model to design ER activities aimed at CT skill development. However, future work should investigate whether teachers can effectively take advantage of the model for their teaching activities. Moreover, other intervention hypotheses have to be explored and tested in order to demonstrate a broader validity of the model.

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Section: Research Questionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fostering computational thinking through educational robotics: a model for creative computational problem solving

et al. 2020

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“…Bumbacher et al (), for example, found that students using a physical lab applied more systematic inquiry behaviour than students who were using a virtual lab, which was then related to being successful on a domain knowledge post test (see Renken & Nunez, , for similar results). To complicate the case further, Bumbacher, Salehi, Wieman, and Blikstein () found indications that there was a subtle interaction between domain characteristics, the laboratory being virtual or real, and students' experimentation strategies. Similar results have recently been reported by Sullivan, Gnesdilow, Puntambekar, and Kim ().…”

Section: Resultsmentioning

confidence: 99%

Moving towards engaged learning in STEM domains; there is no simple answer, but clearly a road ahead

Jong

2019

Computer Assisted Learning

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What is the best approach to educating students is, evidently, the pivotal question in educational research. In the general debate on this question, clear positions are often taken―for example, whether teacher‐led instruction or more student‐directed approaches should be followed. In the current narrative review, this central question and the different stances taken are explored for a specific field of learning, STEM (science, technology, engineering, and mathematics) domains. The current article starts with an argument as to why the traditional, more directive teacher‐led educational approach to STEM learning may not always lead to deep conceptual knowledge and proposes exploring more engaged forms of learning. More specifically, a particular arrangement for engaged learning, inquiry learning, is taken as an example in this exploration. It is argued that the effects of educational methods are influenced by a multitude of (interacting) factors related to student and teacher characteristics, context, domain, frequency of use, timing, and probably more. Therefore, this article tries to outline a more nuanced and balanced stance towards choosing educational approaches. A picture is presented to show that adopting and combining different approaches, at both the lesson and the curricular levels, may be necessary to reach optimal levels of learning. Existing and upcoming technologies may play a decisive role in realizing this more complex, but also more realistic view of learning in STEM.

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“…Modern technological tools represent platforms that can scaffold inquiry processes and produce effective and efficient learning situations for students (De Jong, 2006). Numerous published studies have been conducted to understand different aspects of inquiry processes, instructional guidance and enhancing students' understanding of inquiry processes through online, web-based content or software-based virtual environments (Brenner et al, 2017;Bumbacher, et al, 2017;Geelan & Fan, 2014). Most of these studies were set in learning contexts where teachers were present with students and did not focus on students' independent inquiry learning in a self-directed online environment for learning science concepts.…”

Section: Significance Of the Studymentioning

confidence: 99%

“…Recently, several researchers have attempted to understand students' engagement in online environments. For example, Bumbacher et al (2017) used POE with related pedagogical strategies to investigate students productive inquiry in a manipulative environment (both physical and virtual) to understand how the manipulative environments and their affordances impact on conceptual understanding. They considered the time between experiments as a measure of how intentional learners are in their actions and what concepts they targeted during their inquiry processes to measure the quality of the research experimental process.…”

Section: Pedagogy and Tools Of Scaffoldingmentioning

confidence: 99%

The role of scaffolding in the instructional design of online, self-directed, inquiry-based learning environments: student engagement and learning approaches

Mamun¹

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Tools for Science Inquiry Learning: Tool Affordances, Experimentation Strategies, and Conceptual Understanding

Cited by 46 publications

References 62 publications

Fostering computational thinking through educational robotics: a model for creative computational problem solving

Fostering computational thinking through educational robotics: a model for creative computational problem solving

Moving towards engaged learning in STEM domains; there is no simple answer, but clearly a road ahead

The role of scaffolding in the instructional design of online, self-directed, inquiry-based learning environments: student engagement and learning approaches

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