Journal of Science Education and Technology最新文献

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.