Journal of Science Education and Technology最新文献

The need for well-designed learning experiences about modern, anthropogenic climate change is great. In light of this need, many scholars have looked towards museums, arguing that as trusted institutions of informal learning, museums are uniquely positioned to support public engagement with contentious, impactful issues like climate change. However, while several museum exhibits have emerged over recent years, empirical research on museum-based learning experiences remains quite limited. We take a step towards advancing understanding of museum-based climate change learning through an empirical investigation at a natural history museum in the US. This study examines learners’ collaborative discourse within one exhibit about climate change, a multiplayer video game called Utah Climate Challenge (UCC). Investigating moments of failure and struggle, we analyze learners’ forms of collaboration through moment-to-moment discourse analysis. Findings demonstrate the importance of scaffolding multiple types of collaboration, as well as the potential for a collaborative, museum-based videogame to support learning of important science concepts relevant to climate change.

From the experiential learning perspective, this study investigates middle and high school students (n = 1009) who used an online module to learn about wildfire hazards, risks, and impacts through computational simulations of wildfire phenomena. These students were taught by 18 teachers in urban, rural, and suburban schools across the United States. We analyzed students’ simulation behaviors captured in log files, responses to an assessment administered before and after the module, and demographic surveys, as well as teachers’ responses to a post-module implementation survey. Using mixed effects generalized linear modeling, we investigated whether students’ simulation experiences, their prior real-world wildfire experience, and the strategies used by their teachers predicted their understanding of wildfire concepts. In estimating the effect sizes of these variables, we controlled for student variables such as gender, race, English language status, prior wildfire knowledge (pre-test), and module completion rate. Results indicate that students’ simulation experience and teacher variation were the two most significant effects, followed by students’ real-life wildfire experience. Teacher variations were further explained by differences in teachers’ pedagogical strategies while implementing the module. Implications of these findings are discussed for the design and further research of simulations used as proxies for experiential learning of natural hazards.

According to several studies, the three levels of representation in chemistry are the fundamental aspects of effective learning and understanding of chemistry. In this study, we aim to illustrate how students identify changes in the matter using eye-tracking and verbalizations. Five students observed chemical and physical phenomena depicted by using the three representational levels under eye-tracking monitoring. This allows making inferences about which representation received students’ attention for the longest time. In order to enrich this illustrative experiment, data were triangulated with think-aloud techniques and researchers’ observations during the procedure. Our results suggest that eye-tracking experiments may provide some relevant insights into students’ cognition regarding representational levels. The multiple case study presented hereby pointed out that the levels observed for the longest time were the macro and the submicro levels, although only the macro level was relevant to the student’s answers, according to their verbalizations. Finally, qualitative analyses of these illustrations are also presented and discussed.

As augmented reality (AR) gains prevalence, various AR exhibits are being installed in science museums. However, few research has thus far examined the extent to which these exhibits can improve visitors’ learning. This study qualitatively evaluates the effectiveness of an AR dinosaur exhibit at the Gwacheon National Science Museum in Korea and examines the implications for its improvement. Eight elementary school students experienced the AR dinosaur exhibit, and their reactions were captured by audio and video recordings. Science museum experts were also interviewed to understand the intended affordances of the exhibit. The students’ responses to the intended affordances were examined by analyzing their tour of the AR dinosaur exhibit. We found that the exhibit attracted the visitors by catching their attention. However, they did not pay attention to the exhibition’s primary purpose of improving scientific understanding or reasoning. Some unintended interactions, unrelated to the intended affordances, also emerged. The limitations of the examined AR dinosaur exhibit suggest implications for improving AR exhibits in the future.

Qualified professionals in science, technology, engineering, and mathematics (STEM) and STEM education are in increasingly short supply globally. Role models can help increase women’s representation in STEM, both at entry and senior levels. The study objectives were to identify the characteristics of role models in STEM higher education and careers and to investigate the differences in role model characteristics between career stages and between genders. We used a mixed-methods methodology involving a questionnaire and interviews. The participants, 788 alumni and final-year undergraduate and graduate students from a STEM research university, responded to the questionnaire, and ten leading women in STEM professions were interviewed. The questionnaire results indicated that a higher proportion of women than men reported being influenced by a role model during their studies. Seven key characteristics of role models were identified from the open-ended responses and the interviews: ambitious, charismatic, empathic and encouraging, inspiring, knowledgeable, gifted, and professional. The most frequent characteristics women mentioned were empathic and encouraging. The research findings support and align with the social cognitive career theory (SCCT), demonstrating how role modeling, which is part of the environmental theme, boosts intrinsic motivation—part of the personal theme, for individuals in STEM, especially women. These processes impact women’s determination and professional performance—part of the behavioral theme. Based on our findings, to advance toward a STEM workforce characterized by greater fairness, we recommend designing and deploying structured mentoring programs and forums in STEM departments that can provide young women with more role models for success and thus with more hope for success in these fields.

Assessment feedback is an essential way to promote student learning. Students and teachers may benefit from educational technologies during the feedback process. The purpose of this study was to identify the feedback dimensions that were fulfilled by iPad applications (apps) and to compare teacher practice to the affordances of apps. Typological data analysis was used to perform this qualitative case study. We analyzed seven apps (QR Code Reader, Schoology, Kahoot!, Nearpod, Socrative, ZipGrade, and The Physics Classroom) that a high school physics teacher used to provide feedback in a technology-enhanced classroom. Data sources included classroom video recordings and the websites of these apps. To facilitate the analysis of the data, we enhanced the feedback dimensions identified by Hatzipanagos and Warburton (2009). Our analysis highlighted the diverse capabilities of these apps with regard to supporting the following dimensions of effective feedback: dialogue, visibility, appropriateness, community, power, learning, timeliness, clearness, complexity, reflection, and action. We found that through additional discussion and interactions with students, the teacher could support dimensions that an app did not support. This study not only underscores the critical interplay between technological tools and teacher practices with regard to crafting effective feedback mechanisms but also offers practical recommendations for educators seeking to optimize technology-enhanced feedback in classroom settings. Future research is encouraged to explore the technology implementation experiences of less experienced teachers. Examining teachers working at various school levels and from various countries can offer valuable insights.

The COVID-19 pandemic has drawn the attention of educators to the blended learning model. This study developed a remote blended game-based learning activity that integrates digital game–based learning (DGBL) and blended learning (including online synchronous and asynchronous learning). This method emphasizes that in the online synchronous learning activity, students firstly use mini-educational digital games for group collaborative autonomous pre-learning and then take part in a problem-solving discussion activity guided by the teacher. Afterwards, students complete personal inquiry learning tasks in the asynchronous online activity and conduct asynchronous discussions. This study employed a quasi-experimental design. Participants were 73 senior high school students. The first group used the remote blended game-based learning that integrated DGBL into online synchronous learning. The second group used the face-to-face blended game-based learning approach that integrated DGBL into physical classroom learning. The third group used the remote blended video-based learning that integrated online synchronous video-based learning. The three groups conducted the same online asynchronous inquiry learning tasks. The results found that the remote blended game-based learning activity not only significantly promoted the students’ learning performance in online synchronous learning but also supported their learning performance in online asynchronous learning. Besides, most students’ discussion messages were mostly related to the learning tasks and topic.

With teachers continuing to report challenges in classroom management and difficulties in implementing scientific inquiry, the current manner in which science practical work is conducted in schools suggests the need for added teacher support. In this regard, we can leverage computer vision to provide instructional support by relieving teachers of the need to carry out mundane observations and perform basic interpretations of student activity. However, to our knowledge, little is known about the noticing practices of teachers during practical work, and the support preferences of such a computer vision system have not been studied before. To this end, we recruited 17 science educators with different teaching expertise for a qualitative investigation into the noticing practices and support preferences of science teachers. Results revealed seven major categories and 36 minor categories of student activity that teachers typically observe, which enabled us to derive observation routines that can emulate quality teacher noticing for computer vision input. Our obtained list of observation categories represents a first-of-its-kind list which takes into account concrete noticing practices of science teachers and remains applicable across all types of practical tasks. From participants’ ranking of computer vision models, we further understood the type of computer vision output that teachers prefer for instructional support. To our best of knowledge, no prior research has examined the connection between teacher noticing and computer vision in such detail. Using these findings, we can then pursue the development of computer vision for instructional support in science practical work in an informed manner, taking into account the realities of science laboratories and proclivities of science teachers.

The theoretical framework of communities of practice (CoP) is often used for framing research into online communities. However, there is an absence of measures and empirical work that evaluates knowledge-sharing within such communities. This represents a substantial gap in our understanding of informal learning for diverse people and in the case of communities that support participation in science, a potential loss of capacity for an enterprise that serves a critical function for society. Our objective is to operationalize practice within a designed online, scientific community and evaluate these behaviors as representative of seven theorized high-level groups. For this case study, content and social network analysis were applied to forums (n = 1858), activity posts (n = 1300), and direct messages (n = 667). Content analysis showed that community members most often used practices that were coded as social and not domain-specific. Differences existed in the ways that forums, messages, and activity posts were used as well as between education and outreach members and members of the public and scientists. Social network analysis revealed two domain-specific practices were central to the knowledge-sharing discourse. The seven theorized high-level groups were reduced to three. We provide a new empirically-based framework for use in identifying practices within the digital spaces as well as recommendations for designing online science communities that emphasize knowledge creation.

Mechanistic reasoning about an artifact or system involves thinking about its underlying entities and the properties, activities, and cause-effect relationships of those entities. Previous studies of children’s mechanistic reasoning about engineering solutions have mostly focused on specific mechanical systems such as gear trains. Yet there is growing interest in more contextualized, community-connected engineering design experiences for elementary students. Important questions remain about how the specific features of community contexts influence student opportunities for engineering design practice and reasoning. In this study, we explore whether comparisons in students’ mechanistic reasoning can be made across a range of five different community design contexts. For this qualitative descriptive study, we focus on interview data collected after each of five community-connected engineering-enriched science curriculum units: accessible playground design (3rd grade, N = 8, district A, schools 1 and 2), displaced animal relocation design (3rd grade, N = 10, district A, school 1), migration stopover site design (4th grade, N = 4, district A, school 2), retaining wall design (4th grade, N = 13, district B, school 1), and water filter design (5th grade, N = 9 students, district A, school 3). The findings showed that all students named entities and described entity factors for the design solutions for all five units. For the playground, displaced animals, and stopover sites units, some students described the design artifacts without explicitly expressing connections between entity factors and/or the way factors linked up to the design performance. We argue that particular features of the design tasks influenced students’ approaches to explaining their design solutions. Therefore, we can claim that comparisons can be made across different community-connected engineering design contexts in terms of children’s mechanistic reasoning.