Envisioning Equitable Classrooms That Enhance All Students’ Wonderful Ideas: A Duckworth Perspective

This synopsis centers on Eleanor Duckworth’s ideas about the relationship between education and intellectual development. Specifically, Duckworth described the essence of intellectual development as the “having of wonderful ideas” and the essence of pedagogy as the creation of occasions to “have wonderful ideas.” As opposed to accepting the persistent, pernicious educational belief that there is a single, best way to understand and a single, best way of explaining this understanding, Duckworth determined that all children can come to comparable, equally satisfactory, wonderful understandings when provided occasions to do so.     

Latent inhibition of conditioned disgust reactions in rats

The present experiments, using the latent inhibition (LI) paradigm, evaluated the effect of nonreinforced exposure to saccharin on the acquisition of an LiCl-induced saccharin aversion as measured by conditioned disgust reactions in the taste reactivity test and conditioned taste avoidance in a consumption test. When rats were preexposed to saccharin by bottle exposure (Experiments 1 and 3), LI was evidenced only by conditioned taste avoidance (bottle testing), but not by conditioned disgust reactions (intraoral [IO] testing). On the other hand, when rats were preexposed to saccharin by IO infusion (Experiments 2 and 3), LI was evidenced only by conditioned disgust reactions, but not by conditioned taste avoidance. Experiment 4 showed that LI of conditioned disgust reactions does not appear to be affected by a context shift from preexposure to testing phases. These results show that the expression of LI of both conditioned taste avoidance and conditioned disgust reactions depends critically on a common method of flavor exposure during preexposure and testing.     

Adolescent Sleep Duration,Variability, and Peak Levels of Achievement and Mental Health

To inform public health recommendations for adolescent sleep, the amounts of sleep associated with the highest levels of academic achievement and mental health were examined. The degree to which daily variability in sleep duration represents an underappreciated but functionally significant sleep behavior also was tested. A total of 421 adolescents (M_age = 15.03 years) with Mexican‐American backgrounds reported nightly sleep times for 2 weeks; approximately 80% repeated the same protocol 1 year later. Multilevel modeling indicated that the amount of sleep associated with the lowest levels of internalizing and externalizing symptoms was more than 1 hr greater than the amount associated with the highest levels of academic performance. Greater daily variability in sleep duration predicted greater symptomatology and mixed academic outcomes.     

Predicting Reinforcement and Punishment Behaviors in College Students Coping with Substance Misuse: An Application of Inconsistent Nurturing as Control Theory

Managing a romantic partner’s substance misuse can be challenging, especially in cases where attempts to show support end up worsening the negative behavior. Understanding what might predict one’s actions towards a partner who smokes or drinks can help to alleviate some of the difficulty associated with these interactions. Therefore, this study was designed to examine how issues of undesirable substance use are managed within college students’ romantic relationships. More specifically, the study applied inconsistent nurturing as control theory to assess the extent to which relational uncertainty, perceived network helpfulness, and perceived network hindrance predict the reinforcement and/or punishment of a partner’s smoking or drinking. Results from cross-sectional, self-report survey data (n = 203) revealed that perceived network helpfulness and hindrance were both significant predictors of punishment but not reinforcement. Relational uncertainty was not a significant predictor of reinforcement or punishment. Implications for studying predictors of reinforcement and punishment strategies are discussed, as is the importance of communicating about young adult substance misuse within romantic relationships.     

Keep DRAGging ON: Is solving more problems in DragonBox 12+ associated with higher mathematical performance during the COVID-19 pandemic?

Prior research has shown that game-based learning tools, such as DragonBox 12+, support algebraic understanding and that students' in-game progress positively predicts their later performance. Using data from 253 seventh-graders (12–13 years old) who played DragonBox as a part of technology intervention, we examined (a) the relations between students' progress within DragonBox and their algebraic knowledge and general mathematics achievement, (b) the moderating effects of students' prior performance on these relations and (c) the potential factors associated with students' in-game progress. Among students with higher prior algebraic knowledge, higher in-game progress was related to higher algebraic knowledge after the intervention. Higher in-game progress was also associated with higher end-of-year mathematics achievement, and this association was stronger among students with lower prior mathematics achievement. Students' demographic characteristics, prior knowledge and prior achievement did not significantly predict in-game progress beyond the number of intervention sessions students completed. These findings advance research on how, for whom and in what contexts game-based interventions, such as DragonBox, support mathematical learning and have implications for practice using game-based technologies to supplement instruction.

Practitioner notes

What is already known about this topic

• DragonBox 12+ may support students' understanding of algebra but the findings are mixed.
• Students who solve more problems within math games tend to show higher performance after gameplay.
• Students' engagement with mathematics is often related to their prior math performance.

What this paper adds

• For students with higher prior algebraic knowledge, solving more problems in DragonBox 12+ is related to higher algebraic performance after gameplay.
• Students who make more in-game progress also have higher mathematics achievement, especially for students with lower prior achievement.
• Students who spend more time playing DragonBox 12+ make more in-game progress; their demographic, prior knowledge and prior achievement are not related to in-game progress.

Implications for practice and/or policy

• DragonBox 12+ can be beneficial as a supplement to algebra instruction for students with some understanding of algebra.
• DragonBox 12+ can engage students with mathematics across achievement levels.
• Dedicating time and encouraging students to play DragonBox 12+ may help them make more in-game progress, and in turn, support math learning.

     

Measuring The Business Impact of E‐Learning: An Empirical Study

This study fills a gap in the current HRD literature of return on investment (ROI) analysis of technology‐based learning interventions. Using a Type IV control group method as defined by Wang (2002), the study empirically analyzed and measured the learning effectiveness and the business impact of an e‐learning system implemented in General Electric Company. The e‐learning system under study demonstrated significant economic returns in regard to reduced learning response time and reduced project cycle time. The study shows that e‐learning, as a means of technology‐based HRD intervention, can be highly effective as a performance support learning mechanism, although the results also suggest that e‐learning alone is not sufficient to replace the traditional face‐to‐face learning platforms.     

Assessing approaches to learning with nonparametric multidimensional scaling

This article reports on a trace-based assessment of approaches to learning used by middle school aged children who interacted with NASA Mars Mission science, technology, engineering and mathematics (STEM) games in Whyville, an online game environment with 8 million registered young learners. The learning objectives of two games included awareness and knowledge of NASA missions, developing knowledge and skills of measurement and scaling, applying measurement for planetary comparisons in the solar system. Trace data from 1361 interactions were analysed with nonparametric multidimensional scaling methods, which permitted visual examination and statistical validation, and provided an example and proof of concept for the multidimensional scaling approach to analysis of time-based behavioural data from a game or simulation. Differences in approach to learning were found illustrating the potential value of the methodology to curriculum and game-based learning designers as well as other creators of online STEM content for pre-college youth. The theoretical framework of the method and analysis makes use of the Epistemic Network Analysis toolkit as a post hoc data exploration platform, and the discussion centres on issues of semantic interpretation of interaction end-states and the application of evidence centred design in post hoc analysis.

Practitioner notes

What is already known about this topic

• Educational game play has been demonstrated to positively affect learning performance and learning persistence.
• Trace-based assessment from digital learning environments can focus on learning outcomes and processes drawn from user behaviour and contextual data.
• Existing approaches used in learning analytics do not (fully) meet criteria commonly used in psychometrics or for different forms of validity in assessment, even though some consider learning analytics a form of assessment in the broadest sense.
• Frameworks of knowledge representation in trace-based research often include concepts from cognitive psychology, education and cognitive science.

What this paper adds

• To assess skills-in-action, stronger connections of learning analytics with educational measurement can include parametric and nonparametric statistics integrated with theory-driven modelling and semantic network analysis approaches widening the basis for inferences, validity, meaning and understanding from digital traces.
• An expanded methodological foundation is offered for analysis in which nonparametric multidimensional scaling, multimodal analysis, epistemic network analysis and evidence-centred design are combined.

Implications for practice and policy

• The new foundations are suggested as a principled, theory-driven, embedded data collection and analysis framework that provides structure for reverse engineering of semantics as well as pre-planning frameworks that support creative freedom in the processes of creation of digital learning environments.

     

Understanding how educational maths apps can enhance learning: A content analysis and qualitative comparative analysis

Educational applications (apps) are ubiquitous within children's learning environments and emerging evidence has demonstrated their efficacy. However, it remains unclear what the active ingredients (ie, mechanisms), or combination of ingredients, of successful maths apps are. The current study developed a new, open-access, three-step framework for assessing the educational value of maths apps, comprised of type of app, mathematical content and app design features. When applied to a selection of available maths apps previously evaluated with children in the first 3 years of school (the final sample included 23 apps), results showed that practice-based apps were the most common app type tested (n = 15). Basic number skills, such as number representation and relationships, were the most common area of mathematics targeted by apps (n = 21). A follow-up qualitative comparative analysis showed observed learning outcomes with maths apps were enhanced when apps combined the following: a scaffolded and personalised learning journey (programmatic levelling) and explanations of why answers were right or wrong (explanatory feedback), as well as praise, such as ‘Great job!’ (motivational feedback). This novel evidence stresses the significance of feedback and levelling design features that teaching practitioners and other stakeholders should consider when deciding which apps to use with young children. Directions for future research are discussed.

Practitioner notes

What is already known about this topic

• Educational apps have been shown to support maths attainment in the first 3 years of school.
• Several existing frameworks have attempted to assess the educational value of some of these maths apps.
• Emerging experimental evidence also demonstrates the benefits of specific app design features, including feedback and levelling.

What this paper adds

• Practice-based maths apps are the most common type of app previously evaluated with young children.
• These evaluated maths apps have mostly focused on basic number skills.
• The combination of explanatory and motivational feedback, with programmatic levelling (either dynamic or static), was a necessary condition for enhancing learning outcomes with maths apps.

Implications for practice and policy

• The inclusion of feedback and levelling in maths apps should be considered by app developers when designing apps, and by educational practitioners and parents when deciding which apps to use with their children.
• Further consideration is also needed for the development of educational apps that include a broad range of maths skills.