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This paper makes several considerations for organizing short project-based programming camps to support programming knowledge and motivation. The paper addresses how current research has not explored how summer programming camps helped students not only increase interest to pursue computing career, but also increase their programming knowledge. Informal CS education through summer programming camps provides K-12 students the opportunity to learn how to code through fun and interactive activities outside of their typical classroom experiences. For rural communities with limited computing education resources, summer programming camps may be one of few opportunities to learn about computing. A one-week easy-to-implement programming camp curriculum may help students not only have fun with code but also learn fundamental programming and computational thinking skills through game development. Our annual week-long programming camp at a rural community utilized a project-based learning approach through game development in Python. Findings showed that students were able to achieve basic abstraction and algorithmic thinking but not code analysis and debugging skills. On their motivation to pursue computing careers, results did not show any difference before and after the camp due to their prior existing interest in attending the camp.

Multimedia pedagogical agents are on-screen characters that allow users to navigate or learn in multimedia environments. Several agents’ characteristics may moderate their instructional effectiveness, including appearance, gender, nonverbal communication, motion, and voice. Here, we conducted a meta-analysis to test hypotheses from diverse theories predicting the effects of these agents’ characteristics. We tested predictions of cognitive load theory, cognitive theory of multimedia learning, computers are social actors, social agency theory, uncanny valley, and the action observation network. Our meta-analysis of 32 effect sizes (N = 2104) revealed a small overall effect (g+ = 0.20), showing that learning with multimedia pedagogical agents was more effective than learning without these agents. As predicted by the redundancy effect of cognitive load theory and the coherence principle of cognitive theory of multimedia learning, 2D agents (g+ = 0.38) tended to be more effective than 3D agents (g+ = 0.11). As predicted by the computers are social actors hypothesis, most of the agents’ characteristics, including nonverbal communication, motion, and voice, appeared not to moderate their effectiveness. We conclude that multimedia pedagogical agents help learning through multimedia, and that students may be able to learn similarly from different types of agents.

Emotions can both facilitate and hinder learning. Emotional design features such as colors and shapes can be embedded in multimedia learning environments to manipulate learners’ affects and learning outcomes. However, some studies suggest that emotional designs promote learning, while others show that they hinder it. Although Brom et al. (Educational Research Review 25:100–119, Brom et al. 2018) published a meta-analysis on the use of emotional designs in multimedia learning, an updated search showed that more studies were published recently. Thus, the present meta-analysis is a replication and extension of Brom et al.’s (Educational Research Review 25:100–119, Brom et al. 2018) meta-analysis. A total of 28 articles yielded the following independent effect sizes for each outcome examined: retention (k = 28), transfer (k = 38), comprehension (k = 16), mental effort (k = 28), perceived difficulty (k = 19), change in positive affect (k = 25), intrinsic motivation (k = 28), and liking/enjoyment (k = 19). Results showed that including emotional designs enhanced learning outcomes (retention: g+ = 0.35; transfer: g+ = 0.27; comprehension: g+ = 0.29), change in positive affect (g+ = 0.09), intrinsic motivation (g+ = 0.15), mental effort (g+ = 0.11), liking/enjoyment (g+ = 0.10), and reduced perceived difficulty (g+ = − 0.21). Moderator analyses were conducted for retention, mental effort, intrinsic motivation, and positive affect, and findings showed that mean effect sizes were moderated by participant characteristics as well as methodological and contextual features of the studies. We discuss these findings as well as their theoretical and practical implications.

Integrating dogs into learning environments is becoming more prevalent as growing evidence demonstrates positive benefits of dogs on human functioning. To date, there is no known quantitative revie...

There is widespread evidence showing that concept maps are effective for learning. However, little is known about the effects of various concept map activities. We conducted an experiment to examin...

Signals (or cues) are added to multimedia learning materials to guide learners’ attention to critical elements of the materials. Yet, research on signaling has produced mixed findings on learning outcomes. On the one hand, some studies have reported positive effects of signaling on the performance of learning outcomes (e.g., Jamet in Hum Behav 32:47–53, https://doi.org/10.1016/j.chb.2013.11.013 , 2014). On the other hand, some studies have found that signaling did not improve performance on learning-related outcomes (e.g., Mayer and DaPra in J Exp Psychol 18(3):239–252, https://doi.org/10.1037/a002861670 , 2012). The present meta-analysis seeks to (a) resolve the mixed findings in signaling research, (b) examine the effects on signaling on learning outcomes, and (c) identify potential moderating variables. Following an exhaustive search for studies meeting specified design criteria, 44 independent effect sizes were extracted from 29 experimental studies involving 2726 participants. Studies were coded on features, such as participants (e.g., grade level), presentation (e.g., pacing), and methodology (e.g., quality of the study). Results indicated that signaling is associated with increased learning outcomes (d = .38, p

Studies have shown that learners exposed to interesting and irrelevant information, known as seductive details, do not perform as much as those who learned without seductive details. However, findings are mixed in terms of the degree to which seductive details hinder learning. Further research is also needed on how design features of learning materials influence the seductive details effect. This meta-analysis summarizes the seductive details effect and investigates the moderating factors of design and methodology. We also discuss evidence supporting each of the four hypothetical underlying mechanisms for the seductive details effect. Findings show that including seductive details in learning material can hinder learning. Mean effect sizes were moderated by the presence of seductive details, image type used in comparison, delivery format, language, subject, learner pacing, recall question type, and manipulation check approach. We conclude by highlighting limitations in current research, suggesting opportunities for future research, and examining practical implications.

A large portion of the cost of any software lies in the time spent by developers in understanding a program’s source code before any changes can be undertaken. Measuring program comprehension is not a trivial task. In fact, different studies use self-reported and various psycho-physiological measures as proxies. In this research, we propose a methodology using functional Near Infrared Spectroscopy (fNIRS) and eye tracking devices as an objective measure of program comprehension that allows researchers to conduct studies in environments close to real world settings, at identifier level of granularity. We validate our methodology and apply it to study the impact of lexical, structural, and readability issues on developers’ cognitive load during bug localization tasks. Our study involves 25 undergraduate and graduate students and 21 metrics. Results show that the existence of lexical inconsistencies in the source code significantly increases the cognitive load experienced by participants not only on identifiers involved in the inconsistencies but also throughout the entire code snippet. We did not find statistical evidence that structural inconsistencies increase the average cognitive load that participants experience, however, both types of inconsistencies result in lower performance in terms of time and success rate. Finally, we observe that self-reported task difficulty, cognitive load, and fixation duration do not correlate and appear to be measuring different aspects of task difficulty.

Reform documents like the Next Generation Science Standards call for the integration of science practices and content. One such framework that leverages science practices to support learnin...

Research on smartphone use among college students is extensive. Although numerous studies have examined the relationships between mobile phone use and academic achievements, many such studies have yielded mixed findings. Hence, the overarching goal of this meta-analysis was to comprehensively synthesize existing research to investigate the effects of smartphone addiction on learning. The authors included 44 studies (45 effects) in the analysis yielding a sample size of N ​= ​147,943 college students from 16 countries. The results show that smartphone addiction negatively impacts students' learning and overall academic performance (Q (43) ​= ​711.87, p ​

Studies comparing the instructional effectiveness of dynamic versus static visualizations have produced mixed results. In this work, we investigated whether gender imbalance in the participant samples of these studies may have contributed to the mixed results. We conducted a meta-analysis of randomized experiments in which groups of students learning through dynamic visualizations were compared to groups receiving static visualizations. Our sample focused on tasks that could be categorized as either biologically secondary tasks (science, technology, engineering, and mathematics: STEM) or biologically primary tasks (manipulative–procedural). The meta-analysis of 46 studies (82 effect sizes and 5474 participants) revealed an overall small-sized effect (g+ = 0.23) showing that dynamic visualizations were more effective than static visualizations. Regarding potential moderators, we observed that gender was influential: the dynamic visualizations were more effective on samples with less females and more males (g+ = 0.36). We also observed that educational level, learning domain, media compared, and reporting reliability measures moderated the results. We concluded that because many visualization studies have used samples with a gender imbalance, this may be a significant factor in explaining why instructional dynamic and static visualizations seem to vary in their effectiveness. Our findings also support considering the gender variable in research about cognitive load theory and instructional visualizations.

This experimental study explored the impact of representation + glossary label visuals on science outcomes in a sample of 174 Grade 7 English learners (ELs). Analysis of covariance results indicate...

Instructors often try out innovative interventions (INTRs) in their classrooms to promote student engagement and learning interest. While such efforts are commendable, thinking through how individual and environmental characteristics influence interest development in learners is crucial to meeting such teaching objectives. In this study, we examined the role of personal interest, students’ perceptions of meaningfulness (MNG) and the instructional utility of an innovative hands-on learning module in the development of triggered and maintained situational interests in an engineering classroom that used hands-on learning modules. Participants were undergraduate students enrolled in an engineering classroom who were taught fluid mechanics concepts using an innovative instructional approach. Results of the study indicate that the instructional INTR and the MNG learning material were significant predictors of situational interest. Theoretical and practical implications of the findings are discussed.

Analyzing the process data of students as they complete programming assignments has the potential to provide computing educators with insights into both their students and the processes by which they learn to program. In prior research, we explored the relationship between (a) students’ programming behaviors and course outcomes, and (b) students’ participation within an online social learning environment and course outcomes. In both studies, we developed statistical measures derived from our data that significantly correlate with students’ course grades. Encouraged both by social theories of learning and a desire to improve the accuracy of our statistical models, we explore here the impact of incorporating our predictive measure derived from social behavior into three separate predictive measures derived from programming behaviors. We find that, in combining the measures, we are able to improve the overall predictive power of each measure. This finding affirms the importance of social interaction in the learning process, and provides evidence that predictive models derived from multiple sources of learning process data can provide significantly better predictive power by accounting for multiple factors responsible for student success.

Electric power systems are going through a major upgrade with the integration of advanced technologies to enable the smarter electric grid (SEG). The SEG will use information and communications technology to have enhanced controllability and will become more interactive. This ongoing change also necessitates educating professionals and future generation of engineers to manage evolving complexity of the electric grid. This paper presents experiences in the design and teaching of a unique multidisciplinary team-taught course on smart grid cyber infrastructure to provide a new generation of engineers with a solid foundation of smart grid concepts and their associated challenges. This paper identifies the course topics covered, learning objectives, and assessment activities for the class as well as lessons learned based on course evaluations obtained from multiple offerings. All of the course material is available in public domain and can be easily adopted at another educational institution.

A concept map is a node-link diagram in which each node represents a concept and each link identifies the relationship between the two concepts it connects. We investigated how using concept maps influences learning by synthesizing the results of 142 independent effect sizes (n = 11,814). A random-effects model meta-analysis revealed that learning with concept and knowledge maps produced a moderate, statistically significant effect (g =.58, p < .001). A moderator analysis revealed that creating concept maps (g =.72, p < .001) was associated with greater benefit relative to respective comparison conditions than studying concept maps (g = .43, p

Student retention and learning in STEM disciplines is a growing problem. The 2012 report by the US President's Council of Advisors on Science and Technology (PCAST) predicts a future deficit in science, engineering, and mathematics (STEM) in the following decade and emphasizes the importance of addressing this issue. With this as a motivating factor, the OSBLE+ Social Programming Environment (SPE) was used to leverage social and programming data for the basis of automatically generated prompts inserted into the SPE. These prompts were designed to stimulate help-seeking, help-giving, and social interaction in the learning environment. A social network analysis was performed in order to determine whether exposure to the automated interventions would positively affect the relationship among students over time. Results of this study suggest that students in the experimental treatment who were presented with automated prompts developed more connected and social networks than those in the control treatment.

This meta-analysis synthesized recent research on strategy instruction (SI) effectiveness to estimate SI effects and their moderators for two domains: second/foreign language and self-regulated learning. A total of 37 studies (47 independent samples) for language domain and 16 studies (17 independent samples) for self-regulated learning domain contributed effect sizes for this meta-analysis. Findings indicate that the overall effects of SI were large, 0.78 and 0.87, for language and self-regulated learning, respectively. A number of context (e.g., educational level, script differences), treatment (e.g., delivery agent), and methodology (e.g., pretest) characteristics were found to moderate SI effectiveness. Notably, the moderating effects varied by language versus self-regulated learning domains. The overall results identify SI as a viable instructional tool for second/foreign language classrooms, highlight more effective SI design features, and suggest a need for a greater emphasis on self-regulated learning in SI interventions and research.

Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for Economic Co-operation and Development to examine standard deviation predictors in multilevel models. These predictors and interactions explained additional variation in the dependent variable beyond the control variables. Models using biased and unbiased standard deviations were compared. Meaningful differences were found between the models. Findings supported how standard deviation predictors may increase explanatory power and accuracy of models commonly used in educational research.

The Trauma and Attachment Belief Scale (TABS; Pearlman, 2003) was developed to evaluate levels of cognitive schema disruption in 5 areas (safety, trust, intimacy, control, and esteem) identified by constructivist self-development theory as being sensitive to the effects of trauma. Although the TABS

Although numerous studies have investigated the seductive details effect in multimedia learning and remarked that seductive details can arouse motivation and interest, few studies have examined the seductive details effect using a motivational framework. In order to fill the gap, the present study used a multiple regression model to examine the predictive relationship between four types of interest and post-task performance of participants who received either a passage containing seductive details or a base-only passage. Participants in both groups (N = 258) were asked to learn a passage about geology. An interest questionnaire was validated by using an exploratory factor analysis (EFA). The results of variance analyses showed that the seductive details group rated the learning material significantly higher in triggered situational interest than did the base passage group. Furthermore, the results showed that triggered situational interest mediated the effects of seductive details on recall while there was no mediation effect via maintained situational interest. In addition, emerging and well-developed individual interest moderated the effects of seductive details. In sum, the results indicated that different types of interest play different roles in learning when seductive details are involved. Theoretical and practical implications of the results are discussed and future directions are suggested.

This study used a between-subjects experimental design to examine the effects of three different computer-based instructional strategies (concept map, refutation text, and expository scientific text) on science learning. Concept maps are node-link diagrams that show concepts as nodes and relationships among the concepts as labeled links. Refutational texts are designed specifically to elicit common misconceptions that learners typically hold about a particular topic, directly refute the misconceptions, and present scientific explanations as compelling alternatives. Expository scientific texts consist of texts that are written specifically to present correct scientific information. Sixty-seven participants were randomly assigned to study one of three computer-based presentations on climate change. The dependent measures were tests of free recall and transfer. The concept map group significantly outperformed the refutational and scientific text groups on both free recall and transfer tests. Practical and theoretical implications of these findings are discussed.

Previous work on seductive details has demonstrated that interesting but irrelevant messages hinder students’ text learning. Considering that there is little evidence suggesting the relationship between seductive details and prior knowledge, the present study examined how seductive details affect learning in terms of prior knowledge to address the gap. Using a 2 (prior knowledge: high or low) x 3 (seductive details: not presented, presented first, and presented last) design we asked students (N = 209) drawn from a Chinese middle school to learn a text about the earth. The results showed that, low-prior-knowledge participants reading only base passage outperformed those reading seductive details (regardless of the placement) on both recall and problem-solving performance; High-priorknowledge participants who only read the base passage and those who read seductive details at the end outperformed those who read seductive details first on problem-solving performance. The findings indicate that prior knowledge can compensate the negative effect of seductive details conditionally. Implications for research and practice are delineated and future research directions are presented

Although the seductive details effect, a phenomenon where interesting but irrelevant pictures impede comprehension, is well documented, studies examining ways of moderating its detrimental impact on learning remain few. The present study examined the effect of note-taking on the seductive details effect. Chinese undergraduate participants ( N = 91) were randomly assigned to three conditions that differed in terms of the presence of seductive details and learning strategy (presence or absence of note-taking for the seductive details group). Mediation analyses results showed that seductive details undermined participants' performance on recall and transfer tasks as a result of increased cognitive load. Results from variance analyses indicated that participants in the seductive details and note-taking condition outperformed those in the comparison group and that this effect differed depending on participants' prior knowledge and outcome measures (recall or transfer). Overall, our results suggest that note-taking is an effective cognitive strategy that can help learners overcome the seductive details effect. Implications for theory, practice, and future research are discussed. [ABSTRACT FROM AUTHOR]