For well over a century, the journal Science Education has been publishing articles about the teaching and learning of science. These articles represent more than just a repository of past work: they ...have the potential to offer insights into both the history of science education as well as well as the dynamics of field‐specific change. It can be difficult, however, for educators, researchers, reformers, and policymakers to grasp the nuances of over 100 years of scholarship given the overwhelming amount of textual material. To address this problem, we have used latent Dirichlet allocation, an automated machine‐learning algorithm from the field of natural language processing, to perform an automated literature review and classification of the corpus of work in Science Education. Using this technique, we have classified research in the journal into 21 distinct topics, falling into three thematic groups: science content topics, teaching‐focused topics, and student‐focused topics. We have also quantified the rise and fall of these topics and groups over time, and used them to begin to extract insight into the development of the field, including the effects of national policy changes on topics of interest to the research community, the interrelationships between different research topics, and the effects of intellectual cross‐pollination. Based on this analysis, we argue that this technique shows great promise for even larger‐scale analyses of educational literature and other textual data.
The advancement of underrepresented minority and women PhD students to elite postdoctoral and faculty positions in the STEM fields continues to lag that of majority males, despite decades of efforts ...to mitigate bias and increase opportunities for students from diverse backgrounds. In 2015, the National Science Foundation Alliance for Graduate Education and the Professoriate (NSF AGEP) California Alliance (Berkeley, Caltech, Stanford, UCLA) conducted a wide-ranging survey of graduate students across the mathematical, physical, engineering, and computer sciences in order to identify levers to improve the success of PhD students, and, in time, improve diversity in STEM leadership positions, especially the professoriate. The survey data were interpreted via path analysis, a method that identifies significant relationships, both direct and indirect, among various factors and outcomes of interest. We investigated two important outcomes: publication rates, which largely determine a new PhD student's competitiveness in the academic marketplace, and subjective well-being. Women and minority students who perceived that they were well-prepared for their graduate courses and accepted by their colleagues (faculty and fellow students), and who experienced well-articulated and structured PhD programs, were most likely to publish at rates comparable to their male majority peers. Women PhD students experienced significantly higher levels of distress than their male peers, both majority and minority, while both women and minority student distress levels were mitigated by clearly-articulated expectations, perceiving that they were well-prepared for graduate level courses, and feeling accepted by their colleagues. It is unclear whether higher levels of distress in women students is related directly to their experiences in their STEM PhD programs. The findings suggest that mitigating factors that negatively affect diversity should not, in principle, require the investment of large resources, but rather requires attention to the local culture and structure of individual STEM PhD programs.
Virtual reality (VR) is projected to play an important role in education by increasing student engagement and motivation. However, little is known about the impact and utility of immersive VR for ...administering e-learning tools, or the underlying mechanisms that impact learners' emotional processes while learning. This paper explores whether differences exist with regard to using either immersive or desktop VR to administer a virtual science learning simulation. We also investigate how the level of immersion impacts perceived learning outcomes using structural equation modeling. The sample consisted of 104 university students (39 females). Significantly higher scores were obtained on 11 of the 13 variables investigated using the immersive VR version of the simulation, with the largest differences occurring with regard to presence and motivation. Furthermore, we identified a model with two general paths by which immersion in VR impacts perceived learning outcomes. Specifically, we discovered an affective path in which immersion predicted presence and positive emotions, and a cognitive path in which immersion fostered a positive cognitive value of the task in line with the control value theory of achievement emotions.
The underrepresentation of girls and women in science, technology, engineering, and mathematics (STEM) fields is a continual concern for social scientists and policymakers. Using an international ...database on adolescent achievement in science, mathematics, and reading (N = 472,242), we showed that girls performed similarly to or better than boys in science in two of every three countries, and in nearly all countries, more girls appeared capable of college-level STEM study than had enrolled. Paradoxically, the sex differences in the magnitude of relative academic strengths and pursuit of STEM degrees rose with increases in national gender equality. The gap between boys’ science achievement and girls’ reading achievement relative to their mean academic performance was near universal. These sex differences in academic strengths and attitudes toward science correlated with the STEM graduation gap. A mediation analysis suggested that life-quality pressures in less gender-equal countries promote girls’ and women’s engagement with STEM subjects.
Abstract The paper presents a segment of results obtained within a large study among Czech upper secondary students, whose general aim is to describe teachers’ and students’ views of physics ...experiments (and/or experimenting as such). The participants ( N = 1,325) were asked closed questions concerning how they perceive experiments in physics lessons, how these lessons would look like without experiments and what is the respondents’ personal relation to physics experiments (not necessarily in the school context). Our results show that most often experiments are perceived as an enlivening element in physics lessons, a help with understanding the subject matter and an interesting complement to theory. On the other hand, only a minority of students perceive experiments as a tool physics uses to obtain new information about the world. Around half of the respondents admit that most of their physics lessons would not be affected in any way if experiments were removed. Concerning gender comparison, we found only rare differences at p < 0.05. Similarly, the answers were usually homogeneous across respondents’ year of study; the exceptions are discussed in the paper.
More men are studying and working in science fields than women. This could be an effect of the prevalence of gender stereotypes (e.g., science is for men, not for women). Aside from the media and ...people's social lives, such stereotypes can also occur in education. Ways in which stereotypes are visible in education include the use of gender-biased visuals, language, teaching methods, and teachers' attitudes. The goal of this study was to determine whether science education resources for primary school contained gender-biased visuals. Specifically, the total number of men and women depicted, and the profession and activity of each person in the visuals were noted. The analysis showed that there were more men than women depicted with a science profession and that more women than men were depicted as teachers. This study shows that there is a stereotypical representation of men and women in online science education resources, highlighting the changes needed to create a balanced representation of men and women. Even if the stereotypical representation of men and women in science is a true reflection of the gender distribution in science, we should aim for a more balanced representation. Such a balance is an essential first step towards showing children that both men and women can do science, which will contribute to more gender-balanced science and technology fields.
Computer science and computer science education are marked by gender and racial disparities. To increase the number and diversity of students engaging in computer science, young children need ...opportunities to develop interest and foundational understandings, including computational thinking (CT). Accordingly, elementary teachers need to understand CT, and how to integrate it into their practice. We investigate how to best support elementary teachers in learning to integrate CT into their science teaching through a CT professional development experience for elementary teachers. The professional development consisted of two parts: a professional development workshop and a science teacher inquiry group. In this study, we sought to understand if and how teachers’ views on integrating CT into their teaching practice changed following their participation in a yearlong professional development experience on CT. Based on our analysis, we offer suggestions for future research and implications for the design of professional development for integrating CT into science education.
In recent years, much of the emphasis for transformation of introductory STEM courses has focused on "active learning", and while this approach has been shown to produce more equitable outcomes for ...students, the construct of "active learning" is somewhat ill-defined and is often used as a "catch-all" that can encompass a wide range of pedagogical techniques. Here we present an alternative approach for how to think about the transformation of STEM courses that focuses instead on what students should know and what they can do with that knowledge. This approach, known as three-dimensional learning (3DL), emerged from the National Academy's "A Framework for K-12 Science Education", which describes a vision for science education that centers the role of constructing productive causal accounts for phenomena. Over the past 10 years, we have collected data from introductory biology, chemistry, and physics courses to assess the impact of such a transformation on higher education courses. Here we report on an analysis of video data of class sessions that allows us to characterize these sessions as active, 3D, neither, or both 3D and active. We find that 3D classes are likely to also involve student engagement (i.e. be active), but the reverse is not necessarily true. That is, focusing on transformations involving 3DL also tends to increase student engagement, whereas focusing solely on student engagement might result in courses where students are engaged in activities that do not involve meaningful engagement with core ideas of the discipline.
PDF
