Instructional Science

This article concerns the synergy between science learning, understanding complexity, and computational thinking (CT), and their impact on near and far learning transfer. The potential relationship between computer-based model construction and knowledge transfer has yet to be explored. We studied middle school students who modeled systemic phenomena using the Much.Matter.in.Motion (MMM) platform. A distinct innovation of this work is the complexity-based visual epistemic structure underpinning the Much.Matter.in.Motion (MMM) platform, which guided students' modeling of complex systems. This epistemic structure suggests that a complex system can be described and modeled by defining entities and assigning them (1) properties, (2) actions, and (3) interactions with each other and with their environment. In this study, we investigated students’ conceptual understanding of science, systems understanding, and CT. We also explored whether the complexity-based structure is transferable across different domains. The study employs a quasi-experimental, pretest-intervention-posttest-control comparison-group design, with 26 seventh-grade students in an experimental group, and 24 in a comparison group. Findings reveal that students who constructed computational models significantly improved their science conceptual knowledge, systems understanding, and CT. They also showed relatively high degrees of transfer—both near and far—with a medium effect size for the far transfer of learning. For the far-transfer items, their explanations included entities’ properties and interactions at the micro level. Finally, we found that learning CT and learning how to think complexly contribute independently to learning transfer, and that conceptual understanding in science impacts transfer only through the micro-level behaviors of entities in the system. A central theoretical contribution of this work is to offer a method for promoting far transfer. This method suggests using visual epistemic scaffolds of the general thinking processes we would like to support, as shown in the complexity-based structure on the MMM interface, and incorporating these visual structures into the core problem-solving activities.

As science and technology create an ecosystem that is becoming increasingly more knowledge-intensive, complex, and interconnected, the next generation science standards include systems thinking and systems modeling among 21st skills that should be fostered. We examined the effect of an online cross-disciplinary learning process on the development of systems thinking and modeling skills among engineering students and engineering and science teachers. The study, which used quantitative and qualitative tools, included 55 participants who performed four food-related learning assignments and created conceptual models in Object-Process Methodology. Their responses to online assignments were analyzed along with their perceptions, captured via a reflection questionnaire. The online learning process in this study effectively enhanced systems thinking and modeling skills of all learners, including those with no relevant background. One main conclusion that extends beyond the online learning was that imparting the basics of systems thinking and conceptual modeling skills can be achieved even within a short period of time—less than one semester. The contribution of the study is the formation of theoretical and practical frameworks for the integration of an cross-disciplinary model-based systems engineering online assignments into engineering and science curricula.

Estimating and accounting for statistical uncertainty have become essential in today’s information age, and crucial for cultivating a sound decision making citizenry. Engaging with statistical uncertainty early on can support the gradual development of uncertainty-related considerations that are often challenging to foster at any age. Statistical modeling is a promising introductory practice given the key role played by statistical uncertainty. However, the probabilistic language and tools utilized to formally account for statistical uncertainty are typically seen as insurmountable hurdles to the meaningful engagement of elementary school students. The goal of this article is to demonstrate the pedagogical potential of a particular learning sequence based on an informal adaptation of statistical modeling, integrating student-led real-world investigations and statistical modeling activities. An instrumental case study of a pair of 12-year-old students’ process illustrates how young learners construct informal accounts of statistical uncertainty as they engage in these activities. The discussion centers on the aspects of the learning sequence and guidance that supported their progression.

Open-mindedness is defined as one’s willingness and ability to consider opposing beliefs and perspectives and give them a serious, impartial consideration by setting aside one’s commitment towards one’s own beliefs and perspectives. Learning to prepare and teach open-minded lessons is a crucial skill for student teachers because it fosters an atmosphere in which pupils feel free to express their own views and to learn about the views of others. The aim of this experiment was to examine which instructional strategy best supports student teachers’ learning to prepare an open-minded citizenship education lesson. Therefore, participants (n = 176) processed an instruction on how to prepare an open-minded citizenship education lesson through learning by teaching on video, preparing to teach, or re-study (control condition), and as a post-test designed a lesson plan. We examined the completeness and accuracy of the explanations of the instructional content, feelings of social presence and arousal, open-mindedness levels, the completeness and accuracy of the lesson plans, and the conceptual knowledge of the instructional content. In addition, the lesson plans were graded on overall quality. Results showed that all participants scored higher on open-mindedness as measured with the Actively Open-minded Thinking scale after the experiment than before the experiment. Participants in the control condition prepared significantly more accurate and complete open-minded lessons than participants in the other two conditions, suggesting they have gained better understanding of the instructional content. There were no significant differences between the conditions on the other outcome measures.

When Virtual Reality (VR) is used to present learning content, the three-dimensional image is often not sufficient and additional text is required, either in the form of visual or auditory text. Such additional instructional text could be particularly beneficial due to the many visual stimuli and the risk of visual working memory overload. Relieving working memory by using both channels in the audio-visual presentation, there might be more cognitive capacity available to invest in germane processes for learning. In addition, the image and the text can be processed simultaneously, supporting deeper learning processes. Based on the modality effect, it is therefore assumed that an audio-visual presentation in VR, compared to a visual-only presentation, can lead to higher learning outcomes (recall, comprehension and transfer). In a between-subjects design we analysed the modality principle in VR with 61 subjects (69% female). We hypothesized that when verbal information in VR is given auditorily instead of visually, it leads to overall higher learning outcomes. For intrinsic cognitive load we assumed no differences, but lower extraneous cognitive load and higher germane cognitive load for the audio-visual condition. However, results show a reverse modality effect. The visual-only condition showed higher learning outcome scores for recall, comprehension and transfer. As expected, the conditions showed no differences with regard to the intrinsic cognitive load. However, we also found no differences in extraneous cognitive load. Contrary to our hypothesis we found higher germane cognitive load for the visual-only condition compared to the audio-visual condition, which may be attributed to repeated reading, reading strategies or other self-regulatory strategies. Future research could focus on the use of strategies or evaluate relevant process data.

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.

The “Integrated Development of Key Competences” has been identified as the core idea in education to face competition in the 21st century. Similarly, reform efforts in science education emphasize the importance of integrating scientific practices and disciplinary core ideas. The learning progression (LP) is viewed as a robust tool to facilitate this integrated development. In this study, we integrated learning progressions of energy understanding and scientific explanation into an LP-based intervention to facilitate the instructional design of a middle school energy unit. A quasi-experiment was conducted with 3 teachers and their 184 students to examine the effects of the LP-based intervention on teacher instructional actions and student learning outcomes when compared to traditional instruction. Synthesizing video analysis and pre/posttests, the following results were obtained. (1) LP-based intervention influenced the treatment group’s instructions. (2) The performance of both the treatment and comparison groups of students improved, but students in the treatment group demonstrated a better understanding of energy and were more competent in constructing scientific explanation. The article concludes by discussing implications for the future curriculum design and professional development of teachers.

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.

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.

Hypothesis-based reasoning with conditionals is a skill that is required for engaging in integral activities of modern elementary school science-curricula. The teaching of this skill at this early stage of education, however, is demanding, particularly in whole school classes in which it is difficult to adapt teaching to children’s individual needs. We examine whether a scaffold that is static yet tailored to the context, in which the teacher explicitly models the reasoning process, manages to meet students’ individual cognitive preconditions for learning this skill. Within an inquiry-based learning setting, N = 143 third-graders underwent either an experimental condition in which they received the explicit scaffold, or a control condition in which they did not receive this specific scaffold. Employing a latent transition analysis and a general additive model, it is examined how the additional scaffold interacted with students’ prior knowledge, inhibition ability, and logical reasoning judged by their own teachers. It is found that the additional scaffolds managed to meet the needs of students with little prior knowledge; under the control condition, students with little prior knowledge showed decreased learning achievement, whereas under the experimental condition, students with differing prior knowledge learned to comparable extent and on a higher level. The scaffolds also almost fully diminished a disadvantage for students with lower teacher-judged logical reasoning, and supported students with high inhibition ability in mastering the most difficult aspect of reasoning based on irrelevant evidence. Implications for science education are discussed.

Educating young learners to reason with data is increasingly important given our data-saturated society; yet teachers need support in recognizing and facilitating apt epistemic performance (which involves the beliefs and practices necessary to successfully establish, critique, and use data and knowledge within a domain) regarding data literacy with elementary students. In this exploratory study, we aimed to understand (a) what apt epistemic processes within data literacy look like in practice with children, and (b) to what extent a curriculum built on a simulation-based data analysis intervention (where students engage in experimentation and data analyses through the use of simulations) promotes the epistemic processes of data literacy. We used the Apt-AIR framework, which expounds on the components needed for successful epistemic education, as a tool to identify students’ apt epistemic processes. The results illustrate that elementary students were able to activate cognitive, emotional, and—to a lesser extent—metacognitive and collaborative epistemic processes related to data literacy skills in this context. Additionally, the design features embedded in the experimentation lesson were more successful in engaging students in apt epistemic processes; yet the data analysis lesson, while engaging students in fewer processes overall, was successful in promoting students’ ability to make accurate inferences using an aggregate view of data. We discuss the trends in the apt epistemic processes related to data literacy that emerged and their implications for instruction and learning.

Peer ideas can be valuable contributions to scientific inquiry. Divergent peer ideas can enrich students' thinking and encourage curiosity. Meanwhile, similar peer ideas can promote convergent thinking that can reinforce understanding. However, students need guidance in critically evaluating peer ideas in relation to their own, and in recognizing the influence of peers’ ideas. Guided by the Knowledge Integration framework, we explore whether students’ perceptions of the impact of peers’ ideas align with the revisions made to their written explanations. In a technology-rich, classroom-based inquiry unit on cancer cell division, Grade 7 students (N = 144) investigated the effects of different cancer treatments on cell division, and developed explanations for a recommended treatment. We prompted one group of students to visit a class repository to seek peer ideas similar to their own, and another to seek ideas different from their own. Both groups then revised their recommendations. Based on analyses of students' reflections, initial and revised explanations, and pre and posttests, we found that students prompted to seek divergent ideas perceived peers’ ideas to be more impactful, even though both groups of students revised at the same rate and made similar pre to posttest gains. This study suggests a need to attend to students’ perceptions of the roles of their peers, particularly in environments designed to reflect authentic processes of the social construction of scientific knowledge.

This study examined students’ ability to select relevant ideas from multiple online texts and integrate those ideas in their written products. Students (N = 162) used a web-based platform to complete an online inquiry task in which they read three texts presenting different perspectives on computer gaming and wrote an article for a school magazine on the issue based on these texts. Students selected two snippets from each text during reading and wrote their article with the selected snippets available. The selected snippets were scored according to their relevance for completing the task, and the written products were scored according to their integration quality. The results showed that most students performed well on the selection task. However, nearly half of the written products were characterized by poor integration quality. The hierarchical multiple regression analysis showed that students’ selection of relevant ideas from the texts contributed to their integration of information across texts over and above both reading fluency and reading comprehension skills. The study provides new evidence on the relationship between selection and integration when younger students work with multiple texts, and both theoretical and educational implications of these findings are discussed.

In order to design learning environments that foster students’ research skills, one can draw on instructional design models for complex learning, such as the 4C/ID model (in: van Merriënboer and Kirschner, Ten steps to complex learning, Routledge, London, 2018). However, few attempts have been undertaken to foster students’ motivation towards learning complex skills in environments based on the 4C/ID model. This study explores the effects of providing autonomy, competence and relatedness support (in Deci and Ryan, Psychol Inquiry 11(4): 227–268, https://doi.org/10.1207/S15327965PLI1104_01, 2000) in a 4C/ID based online learning environment on upper secondary school behavioral sciences students’ cognitive and motivational outcomes. Students’ cognitive outcomes are measured by means of a research skills test consisting of short multiple choice and short answer items (in order to assess research skills in a broad way), and a research skills task in which students are asked to integrate their skills in writing a research proposal (in order to assess research skills in an integrative manner). Students’ motivational outcomes are measured by means of students’ autonomous and controlled motivation, and students’ amotivation. A pretest-intervention-posttest design was set up in order to compare 233 upper secondary school behavioral sciences students’ outcomes among (1) a 4C/ID based online learning environment condition, and (2) an identical condition additively providing support for students’ need satisfaction. Both learning environments proved equally effective in improving students’ scores on the research skills test. Students in the need supportive condition scored higher on the research skills task compared to their peers in the baseline condition. Students’ autonomous and controlled motivation were not affected by the intervention. Although, unexpectedly, students’ amotivation increased in both conditions, students’ amotivation was lower in the need supportive condition compared to students in the baseline condition. Theoretical relationships were established between students’ need satisfaction, students’ motivation (autonomous, controlled, and amotivation), and students’ cognitive outcomes. These findings are discussed taking into account the COVID-19 affected setting in which the study took place.

Sourcing - identifying, evaluating, and using information about the sources of information - assists readers in determining what to trust when seeking information on the Internet. To survive in the post-truth era, students should be equipped with sufficient sourcing skills. This study investigated the efficacy of a teacher-led intervention aimed at fostering upper secondary school students’ (N = 365) sourcing during online inquiry. The intervention (4 × 75 min) was structured in accordance with the phases of online inquiry: locating, evaluating, synthesizing, and communicating information. During the intervention, teachers demonstrated why and how to source, and students practiced sourcing by investigating a controversial topic on the Internet. Students worked in small groups and their work was supported with analysis and reflection prompts. Students’ sourcing skills were measured with a web-based online inquiry task before and after the intervention. Compared to controls, the intervention fostered students’ abilities in three of the four skills measured (sourcing in search queries, credibility judgments, and written product). Depending on the sourcing skill, 4–25% of students showed improved performance. The students with low sourcing skills to begin with, benefited the most from the intervention. The study demonstrated that students’ sourcing skills can be supported throughout online inquiry.

Research suggests that explanatory pictures support learning, whereas pictures that distract processing resources from the main ideas of a text may impair learning and are considered as seductive illustrations. However, non-explanatory pictures that are related to the text and that do not tempt readers to focus illustrations more than the text’s main ideas might improve learning through spreading activation processes during learning. This effect might be reflected in memory measures or in metacognitive measures. Therefore, in two experiments, we tested related decorative pictures for positive effects on knowledge and transfer performance and metacognitive monitoring. Results indicate positive effects of related pictures on knowledge acquisition (Experiment 1) and metacognitive monitoring (Experiment 2). In neither experiment, related pictures enhanced transfer performance or interest (measured as triggered and maintained situational interest). This pattern of results can be explained by automatic mutual facilitation of related materials based on spreading activation processes.

We present the analysis of an episode of mathematical problem solving in a group, where data came from multiple advanced recorders, including multiple video cameras, Smartpen recorders, and mobile eye tracking glasses. Analysis focused on a particular group that was ineffective in their problem-solving process. Relying on the commognitive theory of learning on the one hand, and on quantitative descriptors of eye-tracking data on the other hand, we ask how do the interpretations of the discourse analysis and gaze data complement each other in understanding the obstacles to problem-solving in this episode. The setting included four Finnish 9th grade students solving a geometrical problem in the students’ authentic mathematics classroom. The commognitive analysis revealed intensive social communication (subjectifying) along with the mathematical one (mathematizing), which seemed to interfere with the problem-solving process. Specifically, it masked the differences in students’ interpretation of the tasks, and did not allow explication of meta-rules according to which students endorsed mathematical claims. Diagrams of quantified gaze data enabled a more macro-level picture of the full 15 min interaction, revealing differential loci of attention of the group members and thus triangulating the micro-analysis.

We adopted a person-oriented approach to identify patterns of how classroom talk and internal behavioral engagement are combined in students.

The research was conducted on a sample of 639 ninth-grade students (32 classes). We measured the duration of classroom talk for each individual student during Czech language and language arts lessons. The students completed an inventory to determine their internal behavioral engagement. Student achievement was measured using the results from standardized reading literacy tests. We also inquired about the socioeconomic backgrounds of the students.

We identified five distinct participation profiles (eager, chatty, diligent, aloof, and disconnected) and analyzed whether the profiles could predict student achievement. We found that the profile with high talk and high internal behavioral engagement performed best, and the profile with low talk and low internal behavioral engagement performed worst. Analyzing the inconsistent profiles, we found that high internal behavioral engagement did not guarantee student achievement if the engagement was not accompanied by talk. Our findings thus highlight the important role of classroom talk in relation to student learning.

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.

Understanding scientific phenomena requires learners to construct mental models of causal systems. Simulation-based discovery learning offers learners the opportunity to construct mental models and test them against the behavior of a simulation. The purpose of this study was to investigate sequential patterns of learner actions and utterances associated with outcomes of simulation-based guided discovery learning. We conducted a sequence analysis of data gathered from 11 undergraduate students engaged in discovery learning. Three related methods were used for the sequence analysis: Levenshtein edit distance, k-means clustering of the Levenshtein distance, and the Kohonen generalized median sequence. The median sequences of high-gaining and low-gaining participants showed qualitative differences in how they gathered evidence, stated claims, and drew explanatory inferences. Differences between the sequences of actions and utterances of high-gaining and low-gaining participants suggested ways that students might be guided to enhance discovery learning. By tracking the learning patterns of learners, researchers can determine the conditions under which prompts should be provided and offer recommendations for transforming less effective learning strategies to more effective ones.