21st‐century science education digital ecologies: Technology, technique, shoelaces, promise, and pitfalls?

This special issue, Science teaching, learning, and assessment with 21st century, cutting-edge digital ecologies, aimed to examine the use and impact of 21st-century cutting-edge technologies, technological platforms, technological activity, and digital ecologies on science teaching, learning, and assessment. The call for this issue also focused on conceptual and/or critical analyses related to theories and frameworks needed to advance the ways in which digital ecologies and technological activity can transform science teaching, learning, and assessment, as well as the potential of these technologies and platforms to realize equity in access and outcomes in science education for all learners. We sought to feature empirical and conceptual scholarship that would help us to understand how technological advancement in transportation, medicine, agriculture, and science was being translated, adopted, and represented in K-16 formal and informal science teaching and learning. Importantly, we saw this as an opportunity to understand how massive monetary investments in technology-related funding in STEM domains matched the rhetoric that technologies are meant to make learning, among other things, efficient, visual, interesting, dynamic, entertaining, and/or reinforce the tools and practices of science. Overall, the present special issue was an attempt to assess the state of theoretically grounded and rigorous research that is intended to inform how we design, implement, adopt, and enact technological tools and platforms in science classrooms. This was an attempt to understand how the full cycle from conceptualization and design to enactment and impact assessment are undertaken by science education researchers to meet the changing landscape and address the challenges of realizing a literate science populace, racially and linguistically diverse science classrooms, and a robust and inclusive science pipeline, all within a global framework that motivates the work of scientists and science educators. An analysis of technology-related research in the Journal for Research in Science Teaching (JRST) for the last 20 years revealed work related to major domains of practice, which include but are not limited to technology and inquiry (Scalise & Midura, 2018; Waight & Abd-El-Khalick, 2011); teacher education (Bell, Maeng, & Binns, 2013); impact on affective factors; contexts of learning and tools related to disciplinary teaching and learning practices (Nielsen & Hoban, 2015); design-based practices (Lewis, 2006); STEM (Moote, Archer, Dewitt, & MacLeod, 2020); learning and understanding (Liu & Hmelo-Silver, 2009; She & Liao, 2010; Wendt & Rockinson-Szapkiw, 2014); and assessment (Hickey, Taasoobshirazi, & Cross, 2012). In comparison to the above areas of focus, only a few studies focused on equity concerns, and these were primarily gender and language related (Ryoo & Bedell, 2018; Voyles, Fossum, & Haller, 2008). No studies focused on issues of cultural, ethnic, and racial equity and social justice. Similarly, no studies engaged in critiques of technology practice related to teaching and learning. In fact, most studies reported favorable, positive outcomes of technological implementation and enactment. With a broad thematic overlap, these studies reflect the kind of research that is valued by the science education community, for better or for worse. Of significance here is that, in the last 20 years, we have witnessed the exponential growth and development of technologies in science, transportation, and medicine and in our personal lives and popular culture. With this special issue, we wanted to understand the evolution of technology and how understanding of technologies has evolved in parallel with other domains that have significant implications on science education teaching and learning trajectories. Altogether, 45 extended abstracts were submitted in response to JRST's call for special issue manuscripts. Of these, 12 authors and author groups were invited to submit full manuscripts, which were put through the double-blind peer review process. Following multiple rounds of review and revisions, six manuscripts were accepted for final publication. Thematically, the manuscripts focused on social media, teacher professional networks, and Next Generation Science Standards (NGSS); preservice teachers; teacher education, scientific argumentation, and simulated classrooms; computer-based assessment and complex inquiry tasks and log files data to identify student profiles with assessment practices; machine learning (ML) and assessment; serious educational games (SEGs), elementary science, and learning gains; and collaborative inquiry learning, scaffolding, and game-based learning. Learning contexts focused on social media platforms, game-based learning, simulated environments, ML, and computer-based assessment. The research contexts focused on teacher education, pre- and in-service teachers, and students at the elementary and high school levels. To understand professional networks and their role in policy implementation, Rosenberg et al. (2020) analyzed the social structure of the #NGSSchat community via Twitter and focused on members' participation and interactions, the depth and types of conversations, the frequency of some kinds of interactions, and the factors that informed participation over time. The authors argued that the #NGSSchat provides an ideal platform to understand how science education professional networks operate online in the context of large-scale science reforms, such as NGSS. Importantly, the findings revealed that there was a greater number of transactional, social, and substantive conversations and that individuals with varying roles engaged in these conversations. Teachers, researchers, and administrators were the most active participants, and they represented locations that had adopted NGSS. The implications focused on the role and opportunities of social media platforms to foster and promote professional learning related to reform policy adoption and implementation. To address the difficulties of productive scientific argumentation at the elementary level, Mikeska et al. (2020) explored the use of a TeachLive simulated environment as a practice-based space for preservice elementary teachers (PSETs) to engage student avatars in scientific argumentation—argument construction and critique. It was reported that most of the PSETs targeted structural and dialogic components of scientific argumentation in the simulated classroom with more focus on argument construction and less so on argument critique. In general, there was consensus of the value of the TeachLive environment among the PSETS. The implications addressed an important need for the preparation of elementary teachers to enact practices that promote scientific argumentation and, by extension, develop scientific literacy. Furthermore, the simulated environment offered a space for PSETs to practice prior to actual classroom enactment. In order to understand students' interactions while engaging with complex inquiry tasks, Teig et al. (2020) examined students' log files to identify patterns of students' interactions with computer-based assessments and determine if unique characteristics of these interactions emerge as distinct profiles of inquiry performance. The authors argue that the characteristics of these profiles could inform why some students are successful with simulated inquiry tasks compared to students who experienced difficulties. The underlying information could be instructive to support students' understanding of scientific inquiry via computer-based learning environments. The 2015 Norwegian PISA log file data, science performance, and a background questionnaire were analyzed focusing on two inquiry tasks, which involved scientific reasoning, coordinating the effects of multiple variables, and coordinating theory and evidence. The findings reported three distinct profiles of students' inquiry performance: strategic, emergent, and disengaged. These profiles revealed different characteristics of students' exploration behavior, inquiry strategy, time-on-task, and item accuracy. Further analyses showed that students' assignment to these profiles varied according to their demographic characteristics (gender, socioeconomic status, and language at home), attitudes (enjoyment in science, self-efficacy, and test anxiety), and science achievement. This work has implications for understanding student practices with computer-based assessment and support for more effective engagement with complex inquiry tasks. To examine the potential of ML in science education assessment, Zhai et al. (2020) developed a framework to conceptualize ML applications in science assessment. First, 47 studies that applied ML in science assessment were reviewed and classified into five categories: constructed response, essay, simulation, educational game, and neural integrated science. Next, the ML-based and conventional science assessments were compared, and 12 critical characteristics were extracted and used to map three variables in a three-dimensional framework: construct, functionality, and automaticity. Then, 12 characteristics were generated to construct a profile for ML-based science assessments for each article, and these were further analyzed by a two-step cluster analysis. The clusters identified for each variable were summarized into four levels to illustrate the evolution of each. Along with the three-dimensional framework, they proposed five anticipated trends for incorporating ML in science assessment practice for future studies: addressing developmental cognition, changing the process of educational decision-making, personalized science learning, borrowing “good” to advance “good,” and integrating knowledge from other disciplines into science assessment. The implications focus on the potential of ML to redefine science education assessment by addressing developmental cognition in science learning, change the process of educational decision-making, provide personalized science learning, inform good teaching practices, and allow for the integration of interdisciplinary knowledge. To understand how SEGs lead to learning and compare the impact of learning with SEGs versus traditional science learning contexts, Hodges et al. (2020) investigated the learning gains with Virtual Vet, a role-playing SEG designed for elementary students to address the fundamental science concepts associated with the human body systems and the subsequent effect of diabetes and obesity-related illnesses on the given body systems. Two quasiexperimental studies were conducted; for Study 1, students were randomly assigned to play Virtual Vet or participate in guided inquiry lessons that addressed the same objectives. The findings revealed that students in the game condition outperformed the nongame condition. Study 2, which evolved based on the findings of Study 1, compared learning outcomes associated with two conditions: students play only Virtual Vet or students play Virtual Vet and participate in the guided inquiry activities (instructional time was doubled). Interestingly, there was no significant increase in learning gains for the students who participated in both activities. Overall, the findings supported the fact that well-designed SEGs have the potential to facilitate and support science learning in elementary settings. The study suggests that learning environments grounded in pedagogically sound instructional practices have the potential to engender science learning gains for elementary-level students. Noting challenges in scaffolding collaborative inquiry learning in technology-rich environments, Saleh et al. (2020) examined how middle school students from a rural school engaged with CRYSTAL ISLAND: ECOJOURNEYS over a 2-week period. A synergistic scaffolding framework—predefined hard scaffolds and just-in-time soft scaffolds that target the regulation of collaborative inquiry processes and accountable talk—was used to support collaborative inquiry learning. The findings revealed that a fixed-group approach, which leverages multiple perspectives in the form of narrative support, can trigger opportunistic collaboration. Successful collaborative inquiry was also dependent on the synergy between embedded hard scaffolds that targeted sharing, noticing, and evaluation of ideas and soft scaffolds provided by facilitators. The successful uptake of hard and soft scaffolds was dependent on the norms associated with collaborative inquiry and accountable talk. The implications addressed the design of adaptive scaffolds in game-based learning environments. When we examine these thematic trajectories, we are compelled to ask some important questions about the kinds of work that is being done in the domain of science education and technology design, development, implementation, and enactment; learning platforms; and associated activities. To frame the state of scholarship of technology and science education, it is important to examine reform documents. What is the impact of technologies on teachers' practice and students' learning? Repeatedly, we have been witness to the rhetoric that technologies in their myriad forms will revolutionize education, STEM education, and—more specifically—science education. For example, The National Research Council (NRC) (1996) outlined that, for students to develop understandings of science, it is crucial to emphasize the relationship with mathematics and technology. Furthermore, it is noted that “a single problem often has both scientific and technological aspects” (p. 24). Yet, the report makes an explicit distinction between science and technology—in other words, science seeks to understand the natural world, while technology is intended to address human needs. Indeed, in the NRC (1996) report, technology-as-design is discussed in parallel to science as inquiry. Fast forward to the current NGSS (NGSS Lead States, 2013): It is notable that engineering, technology, and applications of science are identified as a major domain to organize disciplinary ideas. In this regard, there is an explicit relationship of science and technology with society. More explicitly, this relationship is discussed in terms of the interdependence of science, engineering, and technology and the influence of engineering, technology, and science on society (STS) and the natural world. In the case of the former, the focus is on the reciprocal relationship of science and technology, the suggestion that these domains inform each other, and that their advancement offers new capabilities and understanding. The influence on the natural world, or STS, focuses on the influence of science, engineering, and technology on society and specifically on domains such as transportation and healthcare that have been informed by the advancements of science and technology. Importantly, there is an explicit recognition that these interactions have “both short- and long-term consequences, positive as well negative, for the health of both people and natural environment” (NGSS, p. 2). This pronouncement is significant because it outlines expectations that are more holistic and realistic, and it aligns with our historical understandings of technological development and evolution (Basalla, 1988; Pacey, 1983). Furthermore, to understand how research related to technology is conceptualized and manifested, it is important to critically revise how technology has been defined in reform documents (Waight & Abd-El-Khalick, 2012). In the framework for K-12 science education (NRC, 2012), “technology is a modification of the natural world made to fulfill human needs or desires” (p. 202). Contrasted with engineering and applications of science, the former addressed the iterative approach involved in designing objects and processes to “meet human needs and wants.” In the case of the application of science, scientific knowledge is used to advance science, engage the process of design, and make predictions about the human impact. 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