Makerspaces, especially in their diverse proliferating forms, support a broad variety of learning outcomes. There is rich work in attempting to understand and describe these learning goals. Yet, there is a lack of support for practitioners and educators to assess the learning in events and programming at makerspaces (and similar environments) without extensive videorecording and documentation. In this paper, we present our design iterations at adapting the Tinkering Studio’s Learning Dimensions Framework (LDF) into tools usable by makerspace facilitators. These tools are intended to support recording observations, to inform the design of events they organize. Coupling an activity theory perspective (Cole and Engeström in The Cambridge handbook of sociocultural psychology. Cambridge University Press, Cambridge, 2007) with Tatar’s (2007) Design Tensions framework, we highlight key categories of considerations that emerge in creating and implementing such an assessment system, namely, tools, terminology, and practice. These interlinked categories foreground the following tensions which expand our considerations for the practice of assessment in makerspaces: supporting real-time, informative observation increases granularity of data collected, but also imposes a cost on facilitator attention; using a common assessment framework across different facilitators requires developing and establishing shared vocabulary and understanding; and tool-driven assessments need repeated adaptation and responsiveness to different facilitator practices. Additionally, this analysis also surfaces the learning for facilitators themselves in such a co-design process of creating and implementing tools to understand, recognize and assess learning experiences through the lenses of personal and shared values around productive learning.
Higher education faculty members incorporate technologies into their teaching and learning practices in higher education for the benefit of their learners. Hence, general technologies, such as presentation software, online classrooms, and learning management systems are ubiquitous in higher education teaching practices. However, emerging technologies (i.e., augmented reality, virtual reality, robotics, tangible user interfaces, wearable technologies, and mixed reality) are not currently in wide use in higher education. As emerging technologies can broaden access to content and increase accessibility for all learners, investigating faculty members’ intention to incorporate these technologies was explored in this study. Faculty participants from higher education institutions (N = 174) completed a 33-item survey, based on the theoretical framework of the decomposed theory of planned behavior. A path analysis of factors that influence faculty members’ intention to integrate emerging technologies in teaching and learning were conducted. Results indicated that attitude, subjective norms, and perceived behavioral control are indicators of intention to use emerging technologies in teaching and learning.
Question-asking is essential for reasoning, understanding, and investigating scientific problems within and beyond traditional classrooms. Nevertheless, questions generated in formal and informal learning environments can be infrequent and unsophisticated. This study explores museum visitors’ question-asking quality by considering their interactions with two different modes of a question-asking mobile app (Ask or Game Mode) in two different museum environments (linear non-interactive or non-linear interactive exhibits). Results showed that visitors’ question-asking quality was influenced by app modes and by museum environments. Specifically, we found that visitors’ question-asking quality was significantly higher when using the gamified version of the app (Game Mode) compared to a non-gamified version (Ask Mode) in a linear non-interactive exhibit. Findings also revealed that question-asking performance could be significantly influenced by instrumental factors (such as app performance in answering questions) and socio-contextual factors (such as visitor group inquiry frequency). The study provides fundamental and comprehensive insights for designing active learning environments by considering the influential factors of question-asking.
In response to the criticism that theory-driven researcher-developed learning tools lack scalability and sustainability in the real world, the design-based implementation research (DBIR) approach was proposed. However, few empirical studies actually describe what a DBIR study looks like and how it can inform readers about learning tool design. We engaged in a retrospective reflection to reconstruct our multi-year DBIR project experience based on team’s research and design documents and artifacts accumulated over 4 years, alongside conversations with the interdisciplinary design team members. Through constant comparison and ethnographic conversations, we describe our project in terms of the five DBIR milestones identified and four design tensions. We discuss how our project showcases evidence of scalability and sustainability of the tool, while effectiveness is addressed differently from design experiments. Implications and future directions are also provided.
The effective application of spherical video-based virtual reality (SVVR) in writing education depends on teachers’ lesson design, which is deeply influenced by their technological pedagogical and content knowledge (TPACK). However, how teaching conceptions, as the fundamental viewpoint that influences teachers’ teaching focuses, shape their TPACK remains uncertain. This study aimed to explore how teachers’ conceptions shape their TPACK regarding SVVR-supported writing instruction. Twenty-one secondary school teachers participated in this study and conducted one semester of SVVR-supported writing lessons. Data were collected through semi-structured interviews, and the interview transcriptions were analyzed using content analysis to explore the association between the teaching conceptions and TPACK. Teaching conceptions were classified into three orientations, namely skill, community, and identity, to reflect the teachers’ teaching focuses. TPACK was classified into three categories, namely Replacement, Amplification, and Transformation, to indicate the levels of integrating SVVR into the writing lessons. The results showed that teachers with students’ identity-focused conceptions shaped their TPACK at the Transformation level of SVVR integration. Teachers with community-focused conceptions developed students’ emotional connections with people and places through their TPACK for deeper writing. Teachers with skill-focused conceptions, on the other hand, shaped their TPACK at the Replacement level that replaced the existing teaching activities and resources with SVVR to teach students writing skills. The findings suggest that teachers may need to shift the conceptions of writing instruction toward identity orientation to develop transformative TPACK.
This study introduced computerized collaboration scripts with an intergroup competition mechanism to foster students’ within-group collaboration in a multi-touch tabletop classroom, investigating whether the scripting effects could be further improved by integrating intergroup competition. As such, this study utilized an experimental design to investigate the effects of intergroup competition on student teamwork performance, collaborative skills and learning achievement. A real-time intergroup competition mechanism was designed and integrated into a scripted multi-touch platform that supported collaborative designs. Forty-nine fifth-grade students from two classes at an elementary school in Taiwan were assigned to distinct groups, with and without intergroup competition. The participating students were required to accomplish a tessellation-related design project in small groups on a multi-touch platform. The findings showed that the students learning with the scripts under intergroup competition on multi-touch tabletop displays demonstrated better teamwork performance, collaborative skills and learning achievement than their counterparts who did not experience intergroup competition. These findings provide empirical evidence as to the effectiveness of integrating collaboration scripts with intergroup competition to computer-supported collaborative learning in multi-touch technology enhanced classrooms, delivering a better understanding of how learning with computerized collaboration scripts can be improved and how group awareness is related to this learning setting.
The worldwide disruption of higher education during the Covid-19 pandemic has been studied from the viewpoints of institutions and teachers, with some attention to students’ health and learning challenges. Attempts to theorise the diverse and conflicting challenges faced by students learning online during the pandemic have been limited. It is helpful to analyse students’ experiences as part of an activity system in order to unravel the system’s elements and determine contradictions that occur. This study adopted a mixed methods approach to investigate students’ online learning experiences at all eight New Zealand universities during the pandemic. Data obtained via a large-scale online survey, followed by focus groups and individual interviews, is presented in light of an Activity Theory framework. Findings show that students’ key challenges were associated with new tools and technologies, lack of interaction and social connection, lack of routine and space, and clashing commitments due to multiple roles and responsibilities. Contradictions can be a driving force for change and development in teaching and learning contexts. We conclude with recommendations for tertiary institutions, teachers, learning designers and students to inform future learning and teaching plans.
Studies that explored intercultural competence in tele collaborative projects mostly integrated their intercultural learning activities in language learning context, and other learning contexts were neglected by researchers. In the present study, we aimed to address this gap by integrating intercultural learning and information literacy learning. We established a common learning space in which students from China and Indonesia learned together to build their information literacy and intercultural competence. A learning activity was designed in which the participants took Informatics course to learn about VR Tour production. They created virtual tours about local cultural attractions, presented them to their foreign peers, and then discussed how tours of each other can be improved. We investigated whether our learning activity can facilitate information literacy about VR Tour production and intercultural competence development. Participants’ perceptions of VR Tour production technology were also explored. Mixed methods research approach was used to collect quantitative and qualitative data. Our results showed that the participants developed their information literacy about VR Tour production and their intercultural competence was promoted. In addition, the participants positively perceived VR Tour production technology. Based on the results, it is suggested that a common learning space can be established in which students from different countries can learn together to build up information literacy and intercultural competence. The findings of the present study can guide educators and researchers in their design of learning activities to help students develop intercultural competence and information literacy skills and use them for communication and exchange of culture-related information.
Videos are an increasingly popular medium for supporting learning in various educational settings. Nowadays, newly designed video-based environments contain enhanced tools that allow for specific interactions with video materials (such as adding annotations and hyperlinks) which may well support generative learning and conceptual understanding. However, to exploit the potentials of such enhanced tools, we need to gain a deeper understanding on the learning processes and outcomes that go along with using these tools. Thus, we conducted a controlled laboratory experiment with 209 participants who were engaged in learning a complex topic by using different enhanced video tools (annotations vs. hyperlinks vs. control group) in different social learning settings (individual vs. collaborative learning in dyads). Findings revealed that participants who learned with hyperlinks and participants in collaborative settings created hypervideo products of higher quality than learners in other conditions. Participants who learned with annotations assessed their knowledge gain higher and had higher results in conceptual understanding when they experienced low cognitive load. With our study we contribute new original work to advance cognitive research on learning with enhanced video learning environments. Limitations and recommendations for future research are discussed.
Facebook is widely used and researched. However, though the data generated by educational technology tools and social media platforms other than Facebook have been used for research purposes, very little research has used Facebook posts as a data source—with most studies relying on self-report studies. While it has historically been impractical (or impossible) to use Facebook as a data source, the CrowdTangle platform allows academic researchers to freely access the massive collection of posts on public Facebook pages and groups. In this paper, we first outline how interactions and textual features in these public Facebook data in concert with established methods from educational data mining and learning analytics can be used to scrutinize educational discourse and knowledge sharing at scale. We then provide a primer that offers considerations for researchers before collecting these data (i.e., conducting research ethically and framing the study). The tutorial also covers matters directly pertaining to using CrowdTangle: accessing the CrowdTangle platform, uploading or identifying pages (or groups), and downloading historical data and it includes code using the statistical software and programming language R. We conclude with ideas for future directions for using Facebook posts as data with a focus on how educational researchers can leverage the scale of the available data and the time periods for which data is available to study educational affairs (i.e., issues or topics) and individuals (i.e., people or organizations) and to scrutinize how Facebook itself is used.
In conventional digital game-based learning, geographic maps are generally used to provide students with the whole picture of the gaming contexts, while the concepts to be learned are separately presented as individual gaming objects. Scholars have indicated the problems of such a gaming content design, in which students could encounter difficulties making effective connections between spatial and conceptual knowledge during the learning process, which may influence their learning effectiveness. As a result, it is a crucial and challenging issue to assist students in organizing spatial and conceptual knowledge in contextual learning environments, such as digital games. To solve this problem, an integrated concept map and geographic map-based digital gaming (CM-GMDG) approach is proposed to demonstrate how spatial and conceptual knowledge can be connected in the development of digital games. To investigate the effectiveness of the approach, a quasi-experiment was conducted in a social science course. Two classes of seventh graders in a high school participated in this study. The experimental group (N = 39) adopted the CM-GMDG approach while the control group (N = 23) adopted the conventional geographic map-based digital gaming (GMDG) approach. The results showed that the students using the CM-GMDG approach significantly outperformed those using the GMDG approach on learning achievement. Moreover, the learning behavioral pattern analysis results showed that compared with the control group, students in the experimental group more frequently engaged in knowledge-acquiring behaviors, such as reading learning materials and completing learning tasks. On the other hand, the control group gave up on the learning tasks more frequently by switching the gaming scenes and stopping answering questions. This indicated that the CM-GMDG approach was more helpful for guiding students to focus on their learning tasks than the GMDG approach.
An important course in the computer science discipline is ‘Data Structures and Algorithms’ (DSA). The coursework lays emphasis on experiential learning for building students’ programming and algorithmic reasoning abilities. Teachers set up a repertoire of formative programming exercises to engage students with different programmatic scenarios to build their know-what, know-how and know-why competencies. Automated assessment tools can assist teachers in inspecting, marking, and grading of programming exercises and also support them in providing students with formative feedback in real-time. This article describes the design of a bespoke automarker that was integrated into the DSA coursework and therefore served as an instructional tool. Activity theory has provided the pedagogical lens to examine how the automarker-mediated instructional strategy enabled self-reflection and assisted students in their formative learning journey. Learner experiences gathered from 39 students enrolled in DSA course shows that the automarker facilitated practice-based learning to advance students know-what, know-why and know-how skills. This study contributes to both curricula and pedagogic practice by showcasing the integration of an automated assessment strategy with programming-related coursework to inform future teaching and assessment practice.
This study is focusing on synthesizing the theoretical and designing framework of constructivist gamification environment models to enhance ill-structured problem solving in learning science. The research model used is based on model development (phase 1) proposed by Richey & Klein. This research consists of two phases as follow: (1) to analyze and synthesize the theoretical framework; (2) to synthesize the designing framework of the constructivist gamification environment model to enhance ill-structured problem solving. The findings of the theoretical analysis shows that the theoretical framework is built upon four main pillars: psychological, pedagogical, technological, and problem-solving bases. Synthesizing the design framework of a development model is based on the findings of theoretical analysis. Five cognitive aspects make up the designing framework: (1) the stimulation of cognitive structure and encouragement of problem solving; (2) the support for cognitive equilibrium; (3) the support for enlarging cognitive structure; (4) the enhancement of ill-structured problem solving; and (5) the support for knowledge construction. The constructivist gamification environment model consists of seven components, namely: (1) the problem base; (2) the learning resource; (3) the cognitive tools; (4) the collaboration; (5) the problem solution; (6) the scaffolding; and (7) the coaching.
This scoping review of research explores the use of educational technologies for adult literacy, specifically for those with low literacy skills. The sample explores research published since 2010 across four major databases, yielding 21 relevant peer-reviewed articles published through the end of 2020. Half of the final included studies were conducted in North America (12 in US and 1 in Canada), and 8 were conducted in other countries around the world. Technology interventions ranged greatly across 15 separate interventions identified, allowing for little to no comparison. Methodologies and quality ranged significantly, with data mining, descriptive surveys, and quasi-experimental designs as the most predominant methods. Instructional strategies ranged greatly as well, from gamification to practice to direct instruction to word highlights. Among the included studies, there is one educational technology that has been studied extensively enough to suggest readiness for scalable implementation and randomized control trials along with promising early results from other interventions. Findings from the scoping review indicate that establishing a research agenda and community in this space, along with future studies detailing participant literacy levels and instructional design features with greater precision, as well as explicitly corresponding design to literacy skills, are significant ways in which educational technology researchers and developers could further the work on this important educational problem.
This paper presents our efforts to develop a scale for measuring students’ learning experiences with knowledge-based chatbots in massive open online courses (MOOCs) through three studies. In Study 1, we conducted a qualitative synthesis of the current literature and analyzed students’ open-ended responses regarding their experiences with a knowledge-based chatbot. Consequently, we identified eight salient domains (i.e., social presence, teaching presence, cognitive presence, self-regulation, co-regulation, perceived ease of use, behavioral intention, and enjoyment), resulting in the creation of 53 items. In Study 2, we selected 30 items that received more than 80% agreement from five experts. Finally, in Study 3, we reported the findings of exploratory and confirmatory factor analyses of the final scale based on student responses (N = 237) and presented 22 items across five domains (i.e., social presence, teaching and cognitive presence, self-regulation, perceived ease of use, and behavioral intention). This research contributes to the current literature by providing an instrument to measure students’ learning experiences with knowledge-based chatbots in MOOCs, which is presently unavailable. The scale developed in this study could be employed for further research aiming to systematically develop knowledge-based chatbots and investigate the relationships between salient factors influencing students’ learning experiences in MOOCs.
This article examines a critical issue in digital literacy assessment design when technological changes are happening with escalating speed in our society. There have been many assessment studies of digital literacy (DL) for diverse purposes and across different geographic and socioeconomic (geo-socioeconomic) contexts. While the assessment framework, instrument design, and technology platforms used for conducting these assessments differ, what remains common is the lack of explicit discussion about the possible role of the technology used and item design in affecting the measure DL. There is an apparent, implicit assumption that DL assessment is similar to the assessment of other academic achievements such as reading literacy and numeracy, which should ideally be measured independent of the specific technologies or task contexts adopted in the assessment. Recent evidence from a United Nations Educational, Scientific and Cultural Organization (UNESCO) commissioned study on a Digital Literacy Global Framework (DLGF) shows that the DL needed to accomplish the same task is heavily dependent on the devices and tools used under different the geo-socioeconomic contexts (Law et al. in A global framework of reference on digital literacy skills for indicator 4.4.2, 2018). Drawing on the DLGF findings and a critical examination of the assessment designs in large-scale international assessment tests, this paper puts forward a product-lifecycle and experience dependence (PLED) perspective to guide the design and interpretation of DL assessment.
Amidst the rapid advancement in the application of artificial intelligence learning, questions regarding the evaluation of students’ learning status and how students without relevant learning foundation on this subject can be trained to familiarize themselves in the field of artificial intelligence are important research topics. This study employed the use of a self-built AI platform (Ladder) for students to systematically learn and apply AI learning model established by the partial least squares (PLS) method to investigate the influence between variables (learning attitudes, self-regulated learning, AI anxiety, individual impact, computational thinking abilities, cognitive styles). This study was particularly conducted in the Department of Computer Science and Information Engineering of a top national university in Southern Taiwan. The valid data were collected from 65 students (55 male students; 10 female students). Furthermore, this study demonstrated the relationship between cognitive style, self-regulated learning and computational thinking. For the first time, it explored the impact of AI anxiety and completed existing research on it. The results of this study show that interest in learning positively affects learning attitudes. In addition, learning attitudes have a positive influence on each individual’s performance. Based on multiple theories and the artificial intelligence learning platform, the model proposed in this study effectively understood students’ learning status.
The use of Experience Sampling Methods (ESM) to assess students’ experiences, motivation, and emotions by sending signals to students at random or fixed time points has grown due to recent technological advances. Such methods offer several advantages, such as capturing the construct in the moment (i.e., when the events are fresh on respondents’ minds) or providing a better understanding of the temporal and dynamic nature of the construct, and are often considered to be more valid than retrospective self-reports. This article investigates the validity and reliability of a variant of the ESM, the DEBE (an acronym for difficult, easy, boring and engaging, and pronounced ‘Debbie’) feedback, which captures student-driven (as and when the student wants to report) momentary self-reports of cognitive-affective states during a lecture. The DEBE feedback is collected through four buttons on mobile phones/laptops used by students. We collected DEBE feedback from several video lectures (N = 722, 8 lectures) in different courses and examined the threats to validity and reliability. Our analysis revealed variables such as student motivation, learning strategies, academic performance, and prior knowledge did not affect the feedback-giving behavior. Monte Carlo simulations showed that for a class size of 50 to 120, on average, 30 students can provide representative and actionable feedback, and the feedback was tolerant up to 20% of the students giving erroneous or biased feedback. The article discusses in detail the aforementioned and other validity and reliability threats that need to be considered when working with such data. These findings, although specific to the DEBE feedback, are intended to supplement the momentary self-report literature, and the study is expected to provide a roadmap for establishing validity and reliability of such novel data types.
This study investigated the impact of participating in a year-long digital-fabrication course on high-school seniors’ problem-solving skills, with a focus on problems involving mechanistic systems. The research questions centered on whether working in a makerspace impacted students’ abilities to solve such problems and whether the process data generated during problem-solving activities could be used to identify the different problem-solving approaches taken by the participants. A novel set of hands-on, mechanistic problems were created to answer these questions, and the results showed that after taking part in the course students performed significantly better on these problems, with the post-course students making more progress towards the solutions than the pre-course students. The process data revealed two distinct problem-solving approaches for each problem, one adopted primarily by experts (the expert approach) and one by pre-course students (the novice approach). The post-course students were more likely to adopt the expert approaches, which were strongly associated with better performance on each problem. The study found that participation in the course made the high-school students better able to “see” the various components and their ways of interacting, making them more like expert engineers.
Students benefit from receiving and providing peer feedback, but the degree of participation limits the benefit. Further, students sometimes resist participation, providing few or only short comments. Prior researchers have examined the role of general attitudes toward peer feedback in limiting participation. However, little research has examined how peer feedback experiences predict the subsequent amount of feedback that students provide to peers. Data on peer feedback experiences and behaviors across multiple assignments were taken from students across two psychology courses (N = 360), two biology courses (N = 483), and one astronomy course (N = 170). The zero-inflated negative binomial (ZINB) regression analyses reveal that receiving fewer critical peer comments in the prior assignment, recognition for higher quality feedback in the prior assignment, and stronger performance on the current assignment predicted higher participation in peer feedback, but norm-setting did not appear to have a role. Implications for practitioners are discussed.
Most social challenges fall outside of the authority of any single individual and therefore require collective action—coordinated efforts by many stakeholders to implement solutions. Despite growing interest in teaching students to lead collective action, we lack models for how to teach these skills. Collective action ostensibly involves design: the act of planning to change existing situations into preferred ones. In other domains, instructors commonly scaffold design using an instructional model known as studio critique in which students strengthen their plans by exchanging arguments with peers and instructors. This study explores whether studio critique can serve as the basis for an effective instructional model in collective action. Using design-based research methods, we designed and implemented scoping deliberations, a new instructional model that augments studio critique with domain-specific templates for planning collective action and repeats weekly to enable iterations. We used process tracing to analyze data from field notes, video, and artifacts to evaluate causal explanations for events observed in this case study. By implementing scoping deliberations in a 10-week undergraduate course, we found that this model appeared effective at scaffolding engagement in planning collective action: students articulated and refined their plans by engaging in argumentation and iteration, as expected. However, students struggled to contact the community stakeholders with whom they planned to work. As a result, their plans rested on implausible, untested assertions. These findings advance instructional science by showing that collective action may require new instructional models that help students to test their assertions against feedback from community stakeholders. Practically, scoping deliberations appear most useful for scaffolding thoughtful planning in conditions when students are already collaborating with stakeholders.
Productive Failure (PF) is an instructional design that implements a problem-solving phase which aims at preparing students for learning from a subsequent instruction. PF has been shown to facilitate students’ conceptual knowledge acquisition in the mathematical domain. Collaboration has been described as a vital design component of PF, but studies that have investigated the role of collaboration in PF empirically so far, were not able to confirm the necessity of collaboration in PF. However, these studies have diverged significantly from prior traditional PF studies and design criteria. Therefore, the role of collaboration in PF remains unclear. In an experimental study that is based on the traditional design of PF, we compared a collaborative and an individual problem-solving setting. It was hypothesized that collaboration facilitates the beneficial preparatory mechanisms of the PF problem-solving phase: prior knowledge activation, awareness of knowledge gaps, and recognition of deep features. In a mediation analysis, the effects of collaborative and individual problem solving on conceptual knowledge acquisition as mediated through the preparatory mechanisms were tested. In contrast to the hypotheses, no mediations or differences between conditions were found. Thus, collaboration does not hold a major preparatory function in itself for the design of PF.
The paper describes an action research being developed by the researcher to address the issue of plagiarism and assist tertiary students to master second-language (L2) writing using sources in a higher education institute (HEI) in Oman. It recruited 16 undergraduate students from two classes who undertook an L2 writing course. To identify their needs of citation skills and develop a follow-up action plan, the students were initially asked to write a referenced-based essay, and then they were interviewed to explore their knowledge and skills of citation. Accordingly, specific amount of tasks were developed and conducted in 10 weeks. After implementing the tasks, the participants were asked to write another referenced-based essay and then they were interviewed for the second time to explore any change they had in knowledge and skills of citation. Findings showed that instances of plagiarism significantly decreased in their second essay; however, there was a modest overall improvement in cases of misinterpreted citations across the students who had low level of English proficiency. Implications for teaching citation skills in academic L2 writing contexts are discussed.
Solving a novel problem has recently garnered some attention as a viable alternative to traditional explicit instruction in the preparation of students for learning. This study investigated the effectiveness of introducing problem-solving tasks and worked examples prior to explicit instruction, along with the use of contrast, for gifted and non-gifted adolescents. One hundred and ninety-nine students from academically selective government and Independent high schools participated in this study. The 2 × 2 × 2 research design that was used examined the effects of giftedness (i.e., gifted vs. non-gifted), instruction-type (i.e., problem-solving vs. worked examples), and structure (i.e., high vs low contrast materials) on the learning outcomes of transfer and procedural knowledge. The study also examined the impact of explicit instruction and invention-first instruction strategies on non-performance variables—self-efficacy, extraneous load, experience of knowledge gaps, and interest. The results of the study suggested that invention-first instruction may be more effective than example-first instruction in transfer, and that gifted students may benefit more from invention-first instruction than example-first instruction. The use of contrast materials was not found to affect performance. Furthermore, instruction was found to have no significant effects on the investigated non-performance variables. Collectively, these findings challenge the conventional teaching modality of explicit instruction in gifted education, and puts forward the possibility of the invention-first strategy as an effective instructional strategy for gifted students.
This paper articulates an approach to incorporating instructor feedback in design-based research. Throughout the process of designing and implementing curriculum to support middle school students’ debugging practices in a summer computer science workshop, our research and practice team utilized instructor-generated conjecture maps as boundary objects, providing insight into the instructors’ reflections on their classroom teaching. We develop an analytic tool for categorizing instructors’ reflections on their conjecture maps, attending specifically to how instructors push back on design choices, whether by envisioning new mediating processes, introducing new connections, discussing new design features, articulating confusion/uncertainty, and/or presenting hopes and predictions. The tool is then applied to seven instructors’ daily reflections over the course of four weeks of instruction, focused on three conjecture maps. Overall, the paper documents a range of tensions that instructors encounter when aiming to provide sustained debugging support to students and introduces a tool for understanding the detailed ways that instructors critique design conjectures.
The present study examines the influence of individual competencies on knowledge integration in inter- and transdisciplinary work. Perspective taking, reflexivity, analogical reasoning, and tolerance of ambiguity and uncertainty were investigated as core competencies for fostering knowledge integration. Additional hypotheses assumed that the positive effects are valid in the scientific and economic contexts and that individual competencies predict knowledge integration at different levels of expertise. To test the hypotheses, 421 participants, comprised of students (N = 165) and individuals working in science (N = 152) and economics (N = 104), answered questionnaires on knowledge integration and competencies of knowledge integration in an online survey. Further questions collected demographic data and inquired about experience and expertise in inter- and transdisciplinary work. The main result was that all postulated competencies positively related to knowledge integration. Analogical reasoning and perspective taking showed the strongest relationships with knowledge integration. Further results show that all competencies are positively related to knowledge integration in the student and expert sample, yet the interrelationships differ between the scientific and economic sample. This investigation into the competencies of knowledge integration contributes to the education of inter- and transdisciplinarians in academia and business practice.
The present study examines the measurement property of instructional quality in mathematics education, building on data from teachers and students, by combing TALIS 2013 and PISA 2012 linkage data from seven countries. Confirmatory factor analysis was applied to examine the dimensionality of the construct instructional quality in mathematics instruction. Three dimensions were identified (i.e., classroom disciplinary climate, teacher support, and cognitive activation) when building on teacher data from TALIS. This three-dimensional model did not fit all countries. When analyzing PISA data, the same three dimensions could be identified, but two additional dimensions appeared: classroom management and student-orientated instruction. This five-dimensional factor structure reflected metric invariance across all countries. The findings imply that students and teachers seem to hold different perceptions about mathematics instructional quality reflect different dimensions. These differences seem to vary within and between countries. This implies that care should be taken when using the construct as an equivalent measure of instructional quality when studying school effectiveness in mathematics education across countries.
Self-explanation prompts in example-based learning are usually directed backwards: Learners are required to self-explain problem-solving steps just presented (retrospective prompts). However, it might also help to self-explain upcoming steps (anticipatory prompts). The effects of the prompt type may differ for learners with various expertise levels, with anticipatory prompts being better for learners with more expertise. In an experiment, we employed extensive modelling examples and different types of self-explanations prompts to teach 78 automotive apprentices a complex and job-relevant problem-solving strategy, namely the diagnosis of car malfunctions. We tested the effects of these modelling examples and self-explanation prompts on problem-solving strategy knowledge and skill, self-efficacy, and cognitive load while learning. In two conditions, the apprentices learned with modelling examples and received either retrospective or anticipatory prompts. The third condition was a control condition receiving no modelling examples, but the respective open problems. In comparison with the control condition, modelling examples did not promote learning. However, we observed differential effects of the self-explanation prompts depending on the learner’s prior knowledge level. Apprentices with higher prior knowledge learned more when learning with anticipatory prompts. Apprentices with less prior knowledge experienced a greater increase in self-efficacy and a higher germane cognitive load when learning with retrospective prompts. These findings suggest using different self-explanation prompts for learners possessing varying levels of expertise.
This study explored the use of an innovative instructional approach called Productive Failure (PF) to design an educational game and its support. The study then examined the effects of two different types of instruction—PF vs. Direct Instruction (DI)—on learning genetics and relevant mathematical knowledge in a Game-Based Learning (GBL) environment. One hundred fifty-seven Year 10 students from two high schools participated in two quasi-experimental studies. The participants were divided into two treatment groups: one group learned targeted concepts using PF with GBL (PF-GBL), while the other group learned the same concepts using DI with GBL (DI-GBL). The results of the first study indicated that the PF-GBL group showed significantly higher learning gains than the DI-GBL group on explanatory genetics knowledge. In the second study, no group difference was found between the PF-GBL group and the DI-GBL group on learning genetics and relevant mathematical knowledge. Implications of findings, limitations, and future research are discussed.
Classroom interactions emerging from socioscientific argumentation may be incompatible with the traditional definitions of learning, thus creating tension and potentially undermining its implementation. Leveraging existing literature, we identify argumentative talk that shifts away from scientific content and toward subjective claims, as well as instances of unproductive argumentation as the points of incompatibility. We contend that attention to the degree of compatibility of enactments of socioscientific argumentation with traditional schooling practices may be necessary for substantive implementation. The role of teachers’ and students’ interactional moves in relation to this compatibility is qualitatively examined using two analytical frameworks related to the content and form of the students’ arguments. To generate practical implications with empirical foundations, compatibility is examined in teacher-led and peer-led argumentation. In teacher-led argumentation, we show that the degree of incompatibility can be managed when teachers extend their elicitation of responses with follow-up interrogative questioning, leading students to rely more on scientific knowledge. In peer-led argumentation, incompatibility can be identified when the argumentation collapses into confrontational disagreement or uncritical agreement, obscuring instances in which students rely on scientific knowledge. We discuss the significance of productive talk moves as a way to advance from incompatibility with traditional schooling toward integrating socioscientific argumentation as a core instructional practice.
Research suggests that troubleshooting activities that require students to reflect on teacher-crafted erroneous examples; i.e., erroneous solutions to problems that correspond to widespread naïve ideas, are beneficial to learning. One possible explanation to these beneficial effects is that troubleshooting activities encourage students to test the quality of their own naïve ideas, not only the ones driving the erroneous examples, thereby improving learning. Few studies have addressed this claim, and the results are inconsistent. These studies, however, were not designed to examine the extent to which students with different naïve ideas benefit from troubleshooting activities. Here, ten 9th grade classes took part in a field experimental study that applied a pre-post-test design after finishing a unit on exponents. Students in each class were randomly assigned to a troubleshooting (114 students) or a self-diagnosis activity (112 students). Self-diagnosis activities are considered to directly nudge students to examine the quality of their own naïve ideas by requiring them to reflect on their solutions. The troubleshooting and self-diagnosis activities both capitalized on the pre-test problems. Both groups increased their proficiency in exponents to a comparable extent from the pre-test to the immediate and the delayed post-test. Troubleshooting students with different naïve ideas detected the errors in the erroneous examples equally well, and their error detection significantly and positively correlated with their self-repair of their own naïve ideas. These findings suggest that all the students benefitted from troubleshooting activities, regardless of whether their own naïve ideas resembled the ones driving the erroneous examples or not.
Responsible citizenship and sound decision-making in today’s information age necessitate an appreciation of the role of uncertainty in the process of generating data-based scientific knowledge. The latter calls for coordinating between different types of uncertainties, related to three types of relevant reasoning: statistical, scientific, and nature of science uncertainties. This article examines separately the uncertainties that young students articulate as they engage in activities designed to concurrently foster all three types of reasoning, and also explores how these different types can interrelate. The context of Citizen Science is particularly suited for this goal, providing a unique pedagogical opportunity for learning scientific content by engaging learners in authentic scientific practices, including data analysis. Based on literature from the three fields of statistics, science and nature of science education, we offer an integrative framework, Deterministic Relativistic and Middle ground (DReaM), which consists of nine sub-categories of uncertainty articulations. We utilize it to analyze an instrumental case study of a pair of middle school students’ (ages 13 and 14) participation in a pilot study of an interdisciplinary extended learning sequence, as part of the Radon Citizen Science Project. The results of an interpretative microgenetic analysis identified all nine DReaM uncertainty articulations sub-categories. These are illustrated in the Findings section with key scenes from the pair’s participation. The discussion depicts how these sub-categories manifested in this particular case study and suggests interrelations between them in a more extended depiction of the DReaM framework. We conclude with the pedagogical implications of the extended framework.
Student-Teacher-Scientist Partnerships (STSPs) provide opportunities for students and teachers to participate in citizen science and engage with scientific concepts and practices, thereby bridging school learning with issues of importance to society, such as climate change. But STSPs require partners to cross boundaries between the cultures of science and schooling, which is extremely difficult. This three-year case study illuminates how successful designers tackled boundary crossing challenges while creating a scalable STSP for environmental education. Analysis of data gathered from three sources – designer-generated documents, interviews with designers, and researchers’ observations of the designer work - through an in-depth participant-observation approach revealed how designers (curriculum writers and partner ecologists) made it possible for middle school students and teachers from partner schools to contribute climate-related data to the ecologists’ research and to other citizen science programs, while accommodating teacher preferences and curricular constraints to pursue educational goals. Findings about how designers used specific methods and created curriculum supports to aid processes of boundary crossing are discussed in light of relevant literature, highlighting their considerations about specific stakeholder needs related to pedagogical, curricular, and scientific goals of the partnership. Further, distilled from the empirical findings and in light of relevant literature are three guidelines in designing for STSPs to foster student inquiry, to support teachers, and to provide multiple benefits through the STSP. These findings and guidelines can help designers anticipate and attend to boundary crossing challenges in STSPs designed for environmental education, with broader implications for science education in general.
In a typical citizen science scenario different groups of people take on various roles in a research process that is often coupled with educational, social or personal objectives. A widely accepted viewpoint asserts that such an endeavor should bring benefits to all involved parties and that no participating individuals should act in service of others or of the end goal. However, the large variety of implementation models, of participating individuals, and of desired impacts, leaves room for inconsistencies regarding what outcomes count towards mutual benefits. In this article we examine the ambiguity embedded in the definition of mutual benefits in citizen science and take a stand towards its resolution. We use school-based citizen science as a model for a multi-stakeholder, multi-objective citizen science. Focusing on teachers and scientists that work together to facilitate student participation in citizen science, nine teacher-scientist pairs that collaborated on nine different school-based projects were included as study participants. We examined participants’ motivations for school-based citizen science and perceived costs and benefits using a questionnaire that they filled while verbally explaining their answers. Our findings reveal multiple ways in which teachers and scientists tapped into their professional, social and personal identities to create multilayered sets of motivations and perceptions of benefits. Thus, we argue that a mutualistic perspective of citizen science should take this complexity into account and be prepared to answer multi-faceted expectations, which may reside not just among but also within participating individuals.
Youth-focused Community and Citizen Science (CCS) projects are contexts in which youth can contribute to the entire “data lifecycle”––from data-collection to decision-making with their scientific findings. But data alone does not contain the answers for what action to take and how. Using the educational context of an afterschool CCS bird monitoring program for 4th and 5th graders, this ethnographic study investigates the different ways youth identified and understood environmental issues on their school campus. We use a theoretical framework of framing, youth identity and agency to understand youth perspectives of their CCS project purpose or goals, their goal-aligned actions (real or imagined), and their CCS practices. We situate these findings within the instructional context of youth’s bird monitoring project and provide instructional recommendations for CCS projects which position youth as knowledge producers, such as how to support youth in developing rigorous intellectual criteria for evaluating their environmental decisions.
This paper presents the results of two community and citizen science research projects – Cities at Play and Community Drive – in which young students (aged 11–15) from vulnerable residential areas in Copenhagen, Denmark, collaborated with architects and urban developers to engage in urban development initiatives in their neighborhoods. An educational design was developed over the two research projects in which students underwent phases of discovery, interpretation, ideation, and experimentation. Data were collected from surveys, observations, and interviews to elucidate the ways that three bridges central to community and citizen science projects can function. These include professional (bridges student learning in school and professional communities outside school), citizen (bridges student learning in school and local communities), and student (bridges student learning in school and new student communities) bridges. This research makes both theoretical and practical advancements. Theoretically, it advances our thinking about the diverse roles that participants in multi-sector partnerships can have, as well as how CCS widens the view of cultural asset-based learning by viewing students as experts of their local communities. Practically, we offer four guidelines that were gleaned from the results that can be instructive for the design of future educational community and citizen science projects.
In the past decade, a growing awareness of citizen science, and the potential of school participation in citizen science (SPICES) has developed. At the heart of any SPICES endeavor lies a partnership representing an unconventional blend of ideas, practices, and agendas, grounded in the realms of both educational practice and scientific research. This paper serves as an introduction to the special issue, substantiating SPICES as a field of research, with conceptualization and exploration of opportunities and tensions as main components. We provide an initial roadmap for future research in the field, with four research trajectories: (a) the notion of mutualism, (b) cognitive challenges that students often face, (c) scientific practices that are uniquely afforded in this field, and how students may be supported in developing them, and (d) emerging design guidelines that can help bridge cultural, epistemic, and organizational gaps within SPICES partnerships. By showing how the six empirical papers that make up this special issue exemplify these trajectories, we claim that SPICES fulfills its literal meaning of a small-in-portion, but significant ingredient within educational systems. SPICES holds the promise of making the grand difference in what schooling can offer students, teachers, communities and society.
Citizen science programs offer opportunities for K-12 students to engage in authentic science inquiry. However, these programs often fall short of including learners as agents in the entire process, and thus contrast with the growing open science movement within scientific communities. Notably, study ideation and peer review, which are central to the making of science, are typically reserved for professional scientists. This study describes the implementation of an open science curriculum that engages high school students in a full cycle of scientific inquiry. We explored the focus and quality of students’ study designs and peer reviews, and their perceptions of open science based on their participation in the program. Specifically, we implemented a human brain and behavior citizen science unit in 6 classrooms across 3 high schools. After learning about open science and citizen science, students (N = 104) participated in scientist-initiated research studies, and then collaboratively proposed their own studies to investigate personally interesting questions about human behavior and the brain. Students then peer reviewed proposals of students from other schools. Based on a qualitative and quantitative analysis of students’ artifacts created in-unit and on a pre and posttest, we describe their interests, abilities, and self-reported experiences with study design and peer review. Our findings suggest that participation in open science in a human brain and behavior research context can engage students with critical aspects of experiment design, as well as with issues that are unique to human subjects research, such as research ethics. Meanwhile, the quality of students’ study designs and reviews changed in notable, but mixed, ways: While students improved in justifying the importance of research studies, they did not improve in their abilities to align methods to their research questions. In terms of peer review, students generally reported that their peers' feedback was helpful, but our analysis showed that student reviewers struggled to articulate concrete recommendations for improvement. In light of these findings, we discuss the need for curricula that support the development of research and review abilities by building on students’ interests, while also guiding students in transferring these abilities across a range of research foci.
The acquisition of online interaction competencies is an important learning objective. The present study explored the relationships between the first-language heterogeneity of computer-supported collaborative learning (CSCL) groups and the development of students’ online interaction self-efficacy via a pretest–posttest design in the context of a nine-week CSCL course. The research participants were 1525 freshmen receiving distance education who were randomly assigned to 343 CSCL groups. Independent of their own language status, students in CSCL groups featuring first-language heterogeneity exhibited lower precourse–postcourse gains in online interaction self-efficacy than students in groups without heterogeneity. Consistent with a theoretically derived moderation model, the relationships between first-language heterogeneity and self-efficacy gains were moderated by the amount of time that the groups spent on task-related communication during the initial collaboration phase (i.e., the relationships were significant when little time was spent on it but not when a great deal of time was spent on it). In contrast, the amount of time that groups spent on communication related to getting to know each other was ineffective as a significant moderator. Follow-up analyses indicated that time spent getting to know each other in first-language heterogeneous CSCL groups seems to have had the paradoxical effect of increasing rather than decreasing perceptions of heterogeneity among group members. Apparently, this effect impaired online interaction self-efficacy gains.
Generative Artificial Intelligence (AI) tools, such as ChatGPT, have received great attention from researchers, the media, and the public. They are gladly and frequently used for text production by many people. These tools have undeniable strengths but also weaknesses that must be addressed. In this squib we ask to what extent these tools can be employed by users for individual learning as well as for knowledge construction to spark a collective endeavor of developing new insights. We take a social, collective notion of knowledge as a basis and argue that users need to establish a dialog that goes beyond knowledge telling (simply writing what one knows) and stimulates knowledge transformation (converting knowledge into complex relational argumentation structures). Generative AI tools do not have any conceptual knowledge or conscious understanding, as they only use word transitions and rely on probabilities of word classes. We suggest, however, that argumentative dialogs among humans and AI tools can be achieved with appropriate prompts, where emergent processes of joint knowledge construction can take place. Based on this assumption, we inquire into the human and into the AI parts of communication and text production. For our line of argument, we borrow from research on individual and collaborative writing, group cognition, and the co-evolution of cognitive and social systems. We outline future CSCL research paths that might take the human-AI co-construction of knowledge into account in terms of terminology, theory, and methodology.
Working solutions to problems are not definitive end points. As a result, code that is technically correct can still be treated as needing revising – a practice in computer programming known as refactoring. We document how late elementary to middle school students and their undergraduate instructors weigh the possibility of refactoring working code in an informal summer computer science workshop. We examined a 20-min stretch of classroom activity in which multiple coding approaches were explicitly evaluated as alternative routes to the same code output. Our theoretical framework draws on the stance triangle, amplifying and attenuating inequity, and an extension of sociomathematical norms. Using the method of interaction analysis, we transcribed and analyzed stretches of talk, gesture, and action during whole class dicourse and small group interactions involving 4–6 students. We investigated how instructors and students introduced, characterized, applied, and contested sociocomputational norms through stancetaking in classroom discourse, which shaped whose voices contributed to the discussion and whose ideas were treated as impactful and praiseworthy in the classroom. Because it is within these discourse spaces that instructors and students interpret and reinterpret sociocomputational norms about what is valued in programming approaches, educational researchers and teachers might attend to these conversation dynamics as one route to fostering more supportive and inclusive learning spaces.
Peer feedback is known to have positive effects on knowledge improvement in a collaborative learning environment. Attributed to technology affordances, class-wide peer feedback could be garnered at a wider range in the networked learning environment. However, more empirical studies are needed to explore further the effects of type and depth of feedback on knowledge improvement. In this mixed method research, 38 students underwent a computer-supported collaborative learning (CSCL) lesson in an authentic classroom environment. Both quantitative and qualitative analyses were conducted on the collected data. Pre- and post-test comparison results showed that students’ conceptual knowledge on adaptations improved significantly after the CSCL lesson. Qualitative analysis was conducted to examine how the knowledge improved before and after the peer feedback process. The results showed that the class-wide intergroup peer feedback supported learners, with improvement to the quality of their conceptual knowledge when cognitive capacity had reached its maximum at the group level. The peer comments that seek further clarity and suggestions prompted deeper conceptual understanding, leading to knowledge improvement. However, such types of feedback were cognitively more demanding to process. The implications of the effects of type of peer feedback on knowledge improvement and the practical implications of the findings for authentic classroom environments are discussed.
Despite their potential to deliver a high-quality learning experience, massive open online courses (MOOCs) pose several issues, such as high dropout rates, difficulties in collaboration between students, low teaching involvement, and limited teacher–student interaction. Most of these issues can be attributed to the large number, diversity, and variation in self-regulated learning (SRL) skills of participants in MOOCs. Many instructional designers try to overcome these issues by incorporating collaborative activities. Others try to scaffold students’ SRL levels by making SRL-focused interventions. However, limited research combines the study of SRL-focused interventions with students’ engagement in collaborative activities, course retention, and learning outcomes of MOOC environments. We deployed a programming-oriented MOOC in which we incorporated chat-based collaborative activities, supported by a learning analytics dashboard. Students were asked to complete SRL-focused questionnaires at the beginning and the end of the course. Based on their score, we calculated an average score that forms their SRL level, creating three groups: (a) control, (b) general intervention, and (c) personalized intervention in which we provided personalized interventions. We compared the students’ learning outcomes, participation in collaborative activities, and retention in the MOOC. These comparisons provided evidence regarding the positive impact of different intervention modes on students’ engagement in collaborative activities and their learning outcomes, with respect to their various SRL profiles. Students allocated to the general and personalized intervention groups displayed increased participation in the collaborative activities and learning outcomes, as compared to students assigned to the control group. We also documented that the SRL interventions positively affected students’ course retention.
Online peer feedback has proven to be practically useful for instructors and to be useful for learning, especially for the feedback provider. Because students can vary widely in skill level, some research has explored matching reviewer and author by performance level. However, past research on the impacts of reviewer matching has found little effect but used a simple binary high–low approach, which may mask the relative benefits of performance matching. In the current study, we leveraged a large dataset involving three large biology courses implementing multiple assignments with online peer feedback. This large dataset enabled dividing students into four levels of relative task performance to tease apart the relative contributions of providing and receiving feedback within the 16 different author–reviewer performance pairings. The results reveal that changes in task performance over assignments attributable to reviewing experiences vary by these finer-grained prior performance distinctions. In particular, providing to students at the same performance level appears to be beneficial, and receiving feedback from students at the same level is helpful except for very low-performing students. A simulation was used to examine the combined effects of receiving and providing under different algorithms for assigning reviewers to documents. The simulations suggest a matching algorithm will produce overall better outcomes than a random assignment algorithm for students at each of the four performance levels.
This study examined students’ understanding of, and reflective inquiry into discourse, specifically their epistemic discourse understanding and meta-discourse, and investigated their roles and relationships in fostering productive inquiry in knowledge building. The participants comprised two classes of ninth grade visual arts students inquiring into art and design. The experimental class (n = 31) engaged in knowledge building using Knowledge Forum® (KF) enriched by meta-discourse involving reflective inquiry and classroom discussion about their discourse. The comparison class (n = 32) similarly worked on KF but using regular classroom discussion. Quantitative analysis indicated that the experimental group students, who engaged in meta-discourse, showed a deeper epistemic discourse understanding and domain knowledge than the comparison students, and that epistemic discourse understanding was associated with productive KF inquiry. Qualitative analysis of the classroom meta-discourse showed that metacognitive reflection, principle-based inquiry, and idea development (i.e., meta-epistemic reflection, meta-epistemic principles, and meta-epistemic theory) support epistemic understanding and productive inquiry. We also discuss the implications of using meta-discourse to enhance epistemic discourse understanding and productive inquiry for knowledge building and computer-supported collaborative learning.
Understanding how individuals collaborate with others is a complex undertaking, because collaborative problem-solving (CPS) is an interactive and dynamic process. We attempt to identify distinct collaborative problem-solver profiles of Chinese 15-year-old students on a computer-based CPS task using process data from the 2015 Program for International Student Assessment (PISA, N = 1,677), and further to examine how these profiles may relate to student demographics (i.e., gender, socioeconomic status) and motivational characteristics (i.e., achieving motivation, attitudes toward collaboration), as well as CPS performance. The process indicators we used include time-on-task, actions-on-task, and three specific CPS process skills (i.e., establish and maintain shared understanding, take appropriate action to solve the problem, establish and maintain team organization). The results of latent profile analysis indicate four collaborative problem-solver profiles: Disengaged, Struggling, Adaptive, and Excellent. Gender, socioeconomic status, attitudes toward collaboration and CPS performance are shown to be significantly associated with profile membership, yet achieving motivation was not a significant predictor. These findings may contribute to better understanding of the way students interact with computer-based CPS tasks and inform educators of individualized and adaptive instructions to support student collaborative problem-solving.