Search

Many studies investigating inquiry learning in science domains have appeared over the years. Throughout this period, inquiry learning has been regularly criticized by scholars who favor direct instruction over inquiry learning. In this vein, Zhang, Kirschner, Cobern, and Sweller (2022) recently asserted that direct instruction is overall superior to inquiry-based instruction and reproached policy makers for ignoring this fact. In the current article we reply to this assertion and the premises on which it is based. We review the evidence and argue that a more complete and correct interpretation of the literature demonstrates that inquiry-based instruction produces better overall results for acquiring conceptual knowledge than does direct instruction. We show that this conclusion holds for controlled, correlational, and program-based studies. We subsequently argue that inquiry-based and direct instruction each have their specific virtues and disadvantages and that the effectiveness of each approach depends on moderating factors such as the learning goal, the domain involved, and students' prior knowledge and other student characteristics. Furthermore, inquiry-based instruction is most effective when supplemented with guidance that can be personalized based on these moderating factors and can even involve providing direct instruction. Therefore, we posit that a combination of inquiry and direct instruction may often be the best approach to support student learning. We conclude that policy makers rightfully advocate inquiry-based instruction, particularly when students’ investigations are supplemented with direct instruction at appropriate junctures.

Background: The use of e-exams in higher education is increasing. However, the role of student diversity in the acceptance of e-exams is an under-researched topic. In the current study, we considered student diversity in terms of three sociodemographic characteristics (age, gender, and second language) and three dispositional student characteristics (computer anxiety, test anxiety, and technology openness). Objectives: The main objective of this study was to investigate the relationship between student diversity and acceptance of e-exams. Methods: Our research combined cross-sectional analyses (N = 1639) with data from a natural experiment on the introduction of e-exams versus the established paper-pencil exams (N = 626) and used both self-report and institutional data. Sociodemographic and dispositional characteristics were indirectly related to pre-exam acceptance via expectancy variables from the Technology Acceptance Model framework. Results and Conclusions: Comparisons of post-exam acceptance showed that practical experience with the e-exam led to a significant increase in e-exam acceptance, and that students with low openness toward technology particularly benefited from this effect. Students' exam performance (i.e., grades) was unrelated to the exam format or their pre-exam acceptance of the e-exam format, and this was true across students' sociodemographic and dispositional characteristics. Takeaway: Student diversity plays a role in e-exam acceptance, but its influence is mitigated by first-hand experience with e-exams. The practical implications for higher education institutions aiming to implement e-exams are discussed.

It is well established in educational research that metacognitive monitoring of performance assessed by self-reports, for instance, asking students to report their confidence in provided answers, is based on heuristic cues rather than on actual success in the task. Subjective self-reports are also used in educational research on cognitive load, where they refer to the perceived amount of mental effort invested in or difficulty of each task item. In the present study, we examined the potential underlying bases and the predictive value of mental effort and difficulty appraisals compared to confidence appraisals by applying metacognitive concepts and paradigms. In three experiments, participants faced verbal logic problems or one of two non-verbal reasoning tasks. In a between-participants design, each task item was followed by either mental effort, difficulty, or confidence appraisals. We examined the associations between the various appraisals, response time, and success rates. Consistently across all experiments, we found that mental effort and difficulty appraisals were associated more strongly than confidence with response time. Further, while all appraisals were highly predictive of solving success, the strength of this association was stronger for difficulty and confidence appraisals (which were similar) than for mental effort appraisals. We conclude that mental effort and difficulty appraisals are prone to misleading cues like other metacognitive judgments and are based on unique underlying processes. These findings challenge the accepted notion that mental effort appraisals can serve as reliable reflections of cognitive load.

In spring 2020, school closures were enacted to slow the spread of the COVID-19 pandemic. Students and teachers faced the challenge of organizing digital teaching and learning without sufficient time to prepare. In this study, we investigated how teachers implemented teaching from a distance and how these different implementations were associated with students' and parents' perceptions of teaching quality and students' social involvement, enjoyment of learning, academic effort, and perceived competence. To this end, we examined data from 277 teachers, 3,159 students in Grades 5 to 10, and 1,688 parents who rated classes in mathematics, German language arts, and English as a foreign language during the school closures. The results showed that teachers' implementations of distance teaching varied greatly. Teaching methods enabling social connectedness (e.g., video meetings, learning videos created by the teacher) revealed the most consistent positive associations with students' and parents' teaching quality ratings and students' learning experiences.

The way medical students learn anatomy is constantly evolving. Nowadays, technologies such as tablets support established learning methods like drawing. In this study, the effect of drawing on a tablet on medical students' anatomy learning was investigated compared to drawing or summarizing on paper. The quality of drawings or summaries was assessed as a measure of the quality of strategy implementation. Learning outcome was measured with an anatomy test, both immediately afterward and after 4-6 weeks to assess its sustainability. There were no significant group differences in learning outcome at both measurement points. For all groups, there was a significant medium strength correlation between the quality of the drawings or summaries and the learning outcome (p < 0.05). Further analysis revealed that the quality of strategy implementation moderated outcomes in the delayed test: When poorly implemented, drawing on a tablet (M = 48.81) was associated with lower learning outcome than drawing on paper (M = 58.95); The latter (M = 58.89) was related to higher learning outcome than writing summaries (M = 45.59). In case of high-quality strategy implementation, drawing on a tablet (M = 60.98) outperformed drawing on paper (M = 52.67), which in turn was outperformed by writing summaries (M = 62.62). To conclude, drawing on a tablet serves as a viable alternative to paper-based methods for learning anatomy if students can make adequate use of this strategy. Future research needs to identify how to support student drawing, for instance, by offering scaffolds with adaptive feedback to enhance learning.

Conducting experiments fosters conceptual understanding in science education. In various studies, combinations of real (hands-on) and virtual (computer-simulated) experiments have been shown to be especially helpful for gaining conceptual understanding. The present systematic review, based on 42 experimental studies, focuses on the following: (1) What is the relative effectiveness of combining real and virtual experiments compared with a single type of experimentation?; and (2) Which sequence of real and virtual experiments is most effective? The results indicate that: (1) in most cases combinations of real and virtual experiments promote conceptual understanding better than a single type of experimentation; and (2) there is no evidence for the superiority of a particular sequence. We conclude that for combining real and virtual experiments, apart from the individual affordances and the learning objectives of the different experiment types, especially their specific function for the learning task must be considered.

Background: Engaging students in computer-assisted guided inquiry learning has great potential to scaffold their scientific understanding: Students are expected to improve their scientific problem-solving skills, and at the same time gain a deep conceptual understanding of the subject-matter. Additional generative activities such as creating video explanations subsequent to inquiry learning activities can also further deepen students' knowledge. Objectives: In this experiment, we therefore compared the effectiveness of computer-based direct instruction (to mimic traditional classroom teaching) versus computer-based inquiry learning. Methods: University students (N = 118) either received video-based direct instruction (direct instruction), including the demonstration of a virtual experiment, or conducted the virtual experiment themselves supported by prompts (inquiry learning). A third group of students additionally generated a video explanation as consolidation activity subsequent to conducting the virtual experiment (inquiry learning + generative activity). Results and Conclusions: Contrarily to our hypotheses, the direct instruction condition outperformed the inquiry learning conditions. There were no significant differences between the inquiry learning and the inquiry learning + generative activity condition. Moderation analyses revealed that the effectiveness of direct instruction predominantly held true for students with low levels of domain-specific self-concept. All in all, our present study contributes to a better understanding of effects of direct instruction versus guided inquiry learning in computer-based science education settings. Importantly, our findings show that the effectiveness of instructional approaches may depend on students' domain-specific self-concept as a motivational prerequisite. As such it is up for further research in science education to identify motivating instructional strategies to enhance students' learning.

Guided inquiry learning is an effective method for learning about scientific concepts. The present study investigated the effects of combining video modeling (VM) examples and metacognitive prompts on university students' (N = 127) scientific reasoning and self-regulation during inquiry learning. We compared the effects of watching VM examples combined with prompts (VMP) to watching VM examples only, and to unguided inquiry (control) in a training and a transfer task. Dependent variables were scientific reasoning ability, hypothesis and argumentation quality, and scientific reasoning and self-regulation processes. Participants in the VMP and VM conditions had higher hypothesis and argumentation quality in the training task and higher hypothesis quality in the transfer task compared to the control group. There was no added benefit of the prompts. Screen captures and think aloud protocols during the two tasks served to obtain insights into students' scientific reasoning and self-regulation processes. Epistemic network analysis (ENA) and process mining were used to model the co-occurrence and sequences of these processes. The ENA identified stronger co-occurrences between scientific reasoning and self-regulation processes in the two VM conditions compared to the control condition. Process mining revealed that in the VM conditions these processes occurred in unique sequences and that self-regulation processes had many self-loops. Our findings show that video modeling examples are a promising instructional method for supporting inquiry learning on both the process and the learning outcomes level.

Background: When interpreting medical images such as dental panoramic radiographs (Orthopanthomogram, OPT), errors are frequent. Previous research has shown that eye movement modelling examples (EMME) are a supportive training method for medical image interpretation to reduce errors. To date, EMME support for OPTs has not been verified. Objectives: We investigated whether a training with EMME and verbal explanations supports dental students in evaluating OPTs. Methods: Dental students were randomly assigned to an intervention (N = 42) or a control group (N = 41). The intervention group received the EMME between pre- and post-test. In a laboratory study, we measured students' gaze behaviour during evaluating OPTs and the detection rate of anomalies. Results and conclusions: The training led to fewer, shorter, and later fixations on anomalies and no difference in visual coverage of the OPT. The detection rate of anomalies did not improve. We replicated the latter finding in an online study (N = 31). Students may not have been able to apply the information from the EMME to detect anomalies. The image reading processes changed to more efficient rather than deeper visual search. Major takeaways: This study evaluated a training method with EMME for anomaly detection of OPTs. EMMEs did not improve the anomaly detection of dental students and changed their visual search process toward a more efficient rather than a deeper search.

Background Improving scientific reasoning and argumentation are central aims of science education. Because of their complex nature, self-regulation is important for successful scientific reasoning. This study provides a first attempt to investigate how scientific reasoning and self-regulation processes conjointly impact argumentation quality. Methods: In a study with university students (N = 30), we used fine-grained process data of scientific reasoning and self-regulation during inquiry learning to investigate how the co-occurrences between scientific reasoning and self-regulation processes are associated with argumentation quality. Findings: When modeling the co-occurrence of scientific reasoning and self-regulation processes using epistemic network analysis, differences between students showing either high or low argumentation quality become apparent. Students who showed high argumentation quality engaged in different scientific reasoning processes together more often than students with low argumentation quality, and they made more connections between self-regulation and scientific reasoning processes. Contribution: These findings offer educational implications for teaching scientific reasoning. Integrating self-regulation and scientific reasoning during instruction could be beneficial for improving scientific reasoning and argumentation.

Citizen Science projects are continuously growing in popularity as they offer a unique possibility to conduct large-scale research projects as well as allow citizens to broaden their knowledge about the research topic or the process of scientific investigations. However, the benefits for participants vary, depending on the way and the amount of participants' personal involvement in the project. In this study, we investigated whether additional guidance would improve involvement and hence lead to greater knowledge gains, higher commitment and improved scientific reasoning of participants in a Citizen Science project on birdwatching. A group receiving guidance was compared to a group which took part in the same project without receiving additional support. Results showed that both groups enhanced their knowledge about birds and their commitment to birding, while there were no significant changes in scientific reasoning. However, participants receiving additional guidance observed a higher number of different bird species and reported being able to identify significantly more species. Participation in a Citizen Science project either with or without further guidance can be seen as powerful in supporting birders at the beginning of their initial stages. Thus, both versions should be taken into account when designing future Citizen Science projects.

Optics is a core field in the curricula of secondary physics education. In this study, we present the development and validation of a test instrument in the field of optics, the ray optics in converging lenses concept inventory (ROC-CI). It was developed for and validated with middle school students, but can also be adapted for the use in higher levels of physics education. The ROC-CI can be used as a formative or a summative assessment of students' conceptual understanding of image formation by converging lenses, assessing the following: (i) the overall understanding of fundamental concepts related to converging lenses, (ii) the understanding of specific concepts, and (iii) students' propensity for difficulties within this topic. The initial ROC-CI consists of 16 multiple-choice items; however, one item was removed based on various quality checks. We validated the ROC-CI thoroughly with distractor analyses, classical test theory, item response theory, structural analyses, and analyses of students' total scores at different measurement points as quantitative approaches, as well as student interviews and an expert survey as qualitative approaches. The quantitative analyses are mostly based on a dataset of N = 318 middle school students who took the ROC-CI as a post-test. The student interviews were conducted with seven middle school students after they were taught the concepts of converging lenses. The expert survey included five experts who evaluated both individual items and the test as a whole. The analyses showed good to excellent results for the test instrument, corroborating the 15-item ROC-CI's validity and its compliance with the three foci outlined above.

Integrating multiple representations into a coherent mental model is one of the challenges when learning with multimedia. In this experimental study (N = 173), we examined how highlighting corresponding information in text-graph learning material can help higher education students to make the necessary connections and improve learning outcomes in two domains. We compared a control condition to a signaling condition with given highlights and an active signaling condition where students were asked to visually highlight corresponding text and graph information themselves. There was no overall benefit of given signals or active signaling. We discuss prior knowledge and the quality of learner-generated signals as possible explanations. For biology learning material, prior knowledge moderated the effect of active signaling. In economics, the effect of prior knowledge was mediated by the quality of learner-generated correspondences. Our findings suggest that different methods of supporting text-graph integration might be useful for different students and learning material.

Background: It is well established that successful learning with multimedia is challenging, especially for younger learners. Aims: It was investigated whether students would profit from instructional support regarding the use of multimedia learning strategies. Sample: Participants were high school students in 8th, 9th, and 10th grade (N = 168). Methods: Participants were assigned to a no-support control group or one of four experimental groups. In the experimental groups, students received either only a multimedia strategy training before learning (training group) or the training was enriched by prompts (prompts before or during learning) or if-then plans (implementation intentions). In the training, multimedia learning strategies were introduced (e.g., linking information from text and picture). The prompts and implementation intentions were aimed at enhancing the application of the multimedia strategies conveyed through the training. Students learned about the process of mitosis by studying multimedia instructions and were tested regarding the acquired knowledge. It was expected that solely training students to use adequate multimedia learning strategies would not promote learning compared with the control group, rather, that additional support like prompts or implementation intentions would be necessary to enhance learning. Results: Although in the experimental groups, multimedia learning strategies were used more frequently especially in the beginning of the instructional unit, there were no effects on learning outcome. Conclusions: Promoting multimedia strategy use did not improve learning. The quality of the different instructional support measures and their suitability for the target groups are discussed as possible explanations for these findings.

We investigated in an experiment with 180 university students the joint role of prior knowledge, alleged model competence, and social comparison orientation regarding the effectiveness of Eye Movement Modeling Examples (EMME) for supporting multimedia learning. EMME consisted of short videos with gaze replays of an instructed model demonstrating effective multimedia processing strategies. Participants were either instructed that the model in the EMME-videos was a successful learner (competent model) or another participant (peer model). Participants in a control condition received no EMME. Furthermore, we activated domain-relevant prior knowledge in half of the participants before watching the EMME. Against our expectations, we found no influence of either prior knowledge activation or model-observer similarity. As expected, our results indicated that EMME fostered multimedia learning. This was also supported by findings from small-scale meta-analyses that were conducted with the focus on the effect of EMME for multimedia learning and potential moderators of the effect. Moreover, results showed first evidence that social comparison orientation interacts with (alleged) model competence regarding the effectiveness of EMME. Further research is needed to follow up on the influence of individual factors as well as social cues on the effectiveness of EMME.

In dental medicine, interpreting radiographs (i.e., orthopantomograms, OPTs) is an error-prone process, even in experts. Effective intervention methods are therefore needed to support students in improving their image reading skills for OPTs. To this end, we developed a compare-and-contrast intervention, which aimed at supporting students in achieving full coverage when visually inspecting OPTs and, consequently, obtaining a better diagnostic performance. The comparison entailed a static eye movement visualization (heat map) on an OPT showing full gaze coverage from a peer-model (other student) and another heat map showing a student's own gaze behavior. The intervention group (N = 38) compared five such heat map combinations, whereas the control group (N = 23) diagnosed five OPTs. Prior to the experimental variation (pre-test) and after it (post-test), students in both conditions searched for anomalies in OPTs while their gaze was recorded. Results showed that students in the intervention group covered more areas of the OPTs and looked less often and for a shorter amount of time at anomalies after the intervention. Furthermore, they fixated on low-prevalence anomalies earlier and high-prevalence anomalies later during the inspection. However, the students in the intervention group did not show any meaningful improvement in detection rate and made more false positive errors compared to the control group. Thus, the intervention guided visual attention but did not improve diagnostic performance substantially. Exploratory analyses indicated that further interventions should teach knowledge about anomalies rather than focusing on full coverage of radiographs.

Dental students commit many errors when diagnosing radiographs. To improve performance, students were asked to compare radiographs (with and without disease or with the same disease); relevant structures were highlighted in the radiographs. In a crossover design, students were randomly assigned to two groups differing in training order: Students in the peripheral-central-group (N = 39) were first trained to detect anomalies in the periphery before receiving training on anomalies in the center; the trainings in the central-peripheral-group (N = 39) were reversed. We measured detection rates and gaze behavior before and after each training. The detection rates after the first training revealed differences in line with our expectations; moreover, when accounting for varying difficulty of the tests sets there were within-groups improvements in the peripheral-central group. Unexpectedly, the gaze behavior was unaffected by the intervention. We discuss shorter learning times and sequence effects as potential causes for our findings.

In multimedia learning, graphs are seen as just one specific instance of pictorial representations requiring the same cognitive processes as realistic depictions. Accordingly, learning from text-graph combinations should also benefit from the same instructional support such as signaling of text-picture correspondences depending on learners' prior knowledge. We investigated whether this expertise reversal of the signaling effect could be replicated for text-graph combinations. Students (N = 101) with different prior knowledge levels learned with text-graph combinations that were either enhanced with signals or not. Results indicate an expertise reversal effect on learning outcomes. A moderated mediation analysis of students' visual attention showed that this pattern could be explained by the fact that students with low prior knowledge (LPK) fixated the graph information earlier, whereas high prior knowledge students fixated the graph later when signals were present. Our results suggest that instructional support should be adapted to students' prior knowledge.

A central factor in research guided by the Cognitive Load Theory (CLT) is the mental effort people invest in performing a task. Mental effort is commonly assessed by asking people to report their effort throughout performing, learning, or problem-solving tasks. Although this measurement is considered reliable and valid in CLT research, metacognitive research provides robust evidence that self-appraisals of performance are often biased. In this review, we consider the possibility that mental effort appraisals may also be biased. In particular, we review signs for covariations and mismatches between subjective and objective measures of effort. Our review suggests that subjective and most objective effort measures appear reliable and valid when evaluated in isolation, because they discriminate among tasks of varying complexity. However, not much is known about their mutual correspondence--that is, whether subjective measures covariate with objective measures. Moreover, there is evidence that people utilize heuristic cues when appraising their effort, similar to utilization of heuristic cues underlying metacognitive appraisals of performance. These cues are identified by exposing biases--mismatch in effects of cue variations on appraisals and performance. The review concludes with a research agenda in which we suggest applying the well-established methodologies for studying biases in self-appraisals of performance in metacognitive research to investigating effort appraisals. One promising method could be to determine the covariation of effort appraisals and objective effort measures as an indicator of the resolution of effort appraisals.

In this study, we investigated whether drawing after learning supports metacognitive monitoring especially when students are supported in their drawing efforts. Therefore, eighty-eight participants were randomly assigned to one of three experimental groups. They were asked to learn from a text comprising five paragraphs about the formation of auroras. After reading each of the five paragraphs, one group had to mentally imagine the contents (control group), a second group had to draw from scratch, and a third group had to draw with the help of spatial scaffolds. All participants provided judgments of learning (JOL) for each paragraph, and took a knowledge test afterwards. Results revealed that students who drew, both with and without scaffold, monitored their learning more accurately on an absolute level. Even though there were no differences between the two drawing conditions for monitoring accuracy, JOLs were based on the actual drawing quality only when students drew with the help of spatial scaffolds. Results thus hint towards the potential of (scaffolded) drawing to support metacognitive monitoring. Reasons for why drawing with spatial scaffolds did not improve monitoring compared to drawing from scratch are discussed.

Digital drawing can foster learning, but only if the drawing is of sufficient quality. Hence, the focus of the present study was to investigate whether and how two types of drawing support may foster drawing quality and, in turn, learning outcomes. To this end, participants (N = 156) were randomly assigned to one of four conditions, in which they either just read text (control), were prompted to make a free-hand representational drawing (unsupported drawing), or they were additionally supported in their drawing efforts because a background (global support) or single elements for the drawing (local support) were already provided. Learning outcomes were assessed by means of recognition, transfer, and a drawing test. Results revealed that students from all three drawing conditions (unsupported, global, and local support) scored better on the transfer and drawing tests than the control condition. Both types of drawing support did neither increase drawing quality nor learning in comparison to unsupported drawing. Reasons for the latter findings are discussed.

Learners face several self-regulatory challenges during multimedia learning: choosing adequate cognitive strategies (cognitive self-regulation), relying on their own learning abilities (motivational self-regulation), and investing sufficient effort (behavioral self-regulation). Implementation intentions (plans that help transform intentions into action) can support self-regulation. We expected that cognitive, motivational, or behavioral implementation intentions improved learning, compared to a control group. In a first experiment, we found weak evidence that cognitive and behavioral implementation intentions improved learning, whereas motivational implementation intentions reduced learning. However, replication failed in two follow-up experiments. Our findings contradict previous research and suggest that implementation intentions are not suitable to support multimedia learning. Future research should focus on possible boundary conditions that could account for the unexpected and unstable findings.

Eye movements reveal what is at the center of people's attention, which is assumed to coincide with what they are thinking about. Eye-movement displays (visualizations of a person's fixations superimposed onto the stimulus, for example, as dots or circles) might provide useful information for diagnosing that person's performance. However, making inferences about a person's task performance based on eye-movement displays requires substantial interpretation. Using graph-comprehension tasks, we investigated to what extent observers (N = 46) could make accurate inferences about a performer's multiple-choice task performance (i.e., chosen answer), confidence, and competence from displays of that person's eye movements. Observers' accuracy when judging which answer the performer chose was above chance level and was higher for displays reflecting confident performance. Observers were also able to infer performers' confidence from the eye-movement displays; moreover, their own task performance and perceived similarity with the performer affected their judgments of the other's competence.

The purpose of this study was to shed light on the cognitive processes underlying the expertise reversal effect related to multimedia signaling. Multimedia signals highlight correspondences between text and pictures, which is supposed to support text-picture integration and thus learning from multimedia. Previous research suggests that learners' prior knowledge moderates the multimedia signaling effect in that they only aid learners with low prior knowledge (LPK). We conducted an eye tracking study with students in secondary education who learned with a digital textbook in one of the two versions: (a) a basic version with mostly text signals only (e.g., bold face), or (b) an extended version with additional multimedia signals that aimed at supporting text-picture integration (e.g., color coding of corresponding text and picture elements). In addition to learning outcomes, we assessed students' cognitive load and gaze behavior as process measures. Results revealed that only LPK learners were supported in learning whereas HPK learners were not affected by multimedia signals (partial expertise reversal). A moderated mediation analysis revealed that multimedia signals affected gaze behavior of LPK students in that they looked earlier at pictures. For high prior knowledge students multimedia signals lead to a higher subjective germane cognitive load. Thus, multimedia signals affected processing of materials. However, the process measures did not explain the expertise reversal of the signaling effect regarding learning outcome.