How effective is instructional support for learning with computer simulations?

The study examined the effects of two different instructional interventions as support for scientific discovery learning using computer simulations. In two well-known categories of difficulty, data interpretation and self-regulation, instructional interventions for learning with computer simulations on the topic “ecosystem water” were developed and tested using a sample of 124 eighth graders in science classes. The results demonstrate the effectiveness of instructional support for domain-specific factual, conceptual, and procedural knowledge acquisition. Students who received either only instructional support for data interpretation or only for self-regulation achieved the highest learning outcomes. However, a combination of instructional support for data interpretation and self-regulation seemed detrimental for knowledge acquisition. Students who received instructional interventions for both data interpretation and self-regulation also showed the highest values of perceived cognitive load. High cognitive load could be a reason for why a combination of particular instructional interventions does not lead to the expected positive learning outcomes.     

Do you think environment protection is more important than economic construction ?Why?

林启锴深圳市汇龙花园It's difficult to tell whether environment protection is more important than economic construction. I think the two issues are equally important, but a good environment is essential to economic construction.     

Should self-regulated learning be integrated with cognitive load theory? A commentary

Research on either cognitive load theory or self-regulated learning usually proceeds without reference to the other theory. In this commentary, we have commented on the editorial introduction and the six papers included in this Special Issue intended to indicate possible links between the two theories. To assist in this process, we have analysed some of the characteristics of both theories that either facilitate or impede the establishment of links. We conclude that while links are possible, the many differences between the theories present considerable barriers that will need to be overcome.     

Cognitive and socio-motivational aspects in learning with animations: there is more to it than ‘do they aid learning or not’

Animations have become a ubiquitous component of computer-based instruction. Despite their widespread use, however, the evidence concerning their effects on learning is rather ambiguous, suggesting that one needs to have a closer look at the conditions under which animations will aid learning. Accordingly, three sets of moderating variables were identified: (1) the degree of processing support that is used to enhance learning with animation, (2) the context in which the animation is being used (e.g., laboratory setting versus classroom), and (3) the domain that is illustrated by the animation. On the one hand, the studies reported in the current special issue investigate manipulations of these variables. On the other hand, the studies vary among each other with respect to these factors, thereby reflecting the enlarged range of current animation research.     

Time is even more important than money

喻彻谕茄碗扁缸痴漏屁铸T属;二六锰言轰品{{鑫云高{益祷去硫诚认赫拓偏黑{认碗漏五俞i后舀i)漏获讥痴赫痴…漏藏扭而蔚从{{布俞i而磁燕茹碱)娜踢瘫必痴益交i)韶夏淞涵痴诚球筛如命哑查;如磷或瘫而赫宕如嵌油余立丘贡备命才晶漏而坛;丧)瑞病而茄介注石t偏云偏碳…惠豁黑黑黑蕊希产添琳福稿诉,赤而翻品)弃福漏赫拓爪偏月点而、奋石俪。、示、,台舜而。p劫娜烹然糕森铆鲜吟卿份峥今扭 脚勿moll竹W.{吮黑Time is even more important than money@杨晓红     

Why do women more often intend to study abroad than men?

Higher Education - In many Western countries, women are more likely to study abroad than men. At present, there is a lack of theory-guided empirical studies searching explanations for this pattern....     

What can moment-by-moment learning curves tell about students’ self-regulated learning?

Many students in primary education learn arithmetic using adaptive learning technologies (ALTs) on tablets every day. Driven by developments in the emerging field of learning analytics, these technologies adjust problems based on learners' performance. Yet, until now it is largely unclear how students regulate their learning with ALTs. Hence, we explored how learners regulate their effort, accuracy and learning with an ALT using moment-by-moment learning curves. The results indicated that moment-by-moment learning curves did reflect students’ accuracy and learning, but no associations with effort were found. Immediate drops were associated with high prior knowledge and suboptimal learning. Immediate peaks were associated with robust learning and pointed to effective student regulation. Close multiple spikes showed moderate learning and lower initial levels of accuracy but, with system support, these students seemed able to regulate their learning. Separated multiple spikes indicated reduced learning and accuracy and potentially signal the inability of students to regulate their learning. In this light, moment-by-moment learning curves seem to be valuable indicators of accuracy regulation during learning with ALTs and could potentially be used in interventions to support SRL with personalized visualizations.     

More student trust,more self-regulation strategy? Exploring the effects of self-regulatory climate on self-regulated learning

Self-regulated learning has been one of the important areas in educational research. The authors adopted structural equation modeling to explore and compare the impacts of three aspects of self-regulatory climate (i.e., academic emphasis, teacher trust, and student trust) on three features of self-regulated learning (i.e., self-efficacy, intrinsic motive, and self-regulation strategy). The results revealed both direct effects of academic emphasis on students’ use of self-regulation strategy, and indirect effects mediated by self-efficacy and intrinsic motive. Teacher trust has a positive impact on self-efficacy. While student trust has a positive impact on intrinsic motive, its relationship with self-regulation strategy is negative. Significant differences in school levels and gender were identified. The findings indicate that students in different cultures may have different expectations for teachers’ support in learning, which in turn influence the relationship between student trust in teachers and the use of self-regulation strategy. Implications for cultivating self-regulated learners are discussed in the article.     

For which students with learning disabilities are self-concept interventions effective?

We have previously conducted a meta-analysis of outcomes of school-based interventions aimed at enhancing the self-concept of students with learning disabilities (LD). This study extends the previous findings by analyzing intervention effect sizes in relation to students' levels of self-concept prior to intervention. The results of these analyses indicated that only groups of students with documented low self-concept benefited significantly from intervention. For these students, intervention effects were much larger than the effects previously estimated from aggregations that included groups with wide-ranging or unknown levels of self-concept prior to intervention. These findings underscore the need for researchers and practitioners to identify students for self-concept intervention based on their documented need, rather than assuming a need based on the students' identification as students with LD.     

Training self-regulated learning skills with video modeling examples: Do task-selection skills transfer?

Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and task-selection, is effective for improving adolescents’ problem-solving posttest performance after self-regulated learning. In these examples, the models used a specific task-selection algorithm in which perceived mental effort and self-assessed performance scores were combined to determine the complexity and support level of the next task, selected from a task database. In the present study we aimed to replicate prior findings and to investigate whether transfer of task-selection skills would be facilitated even more by a more general, heuristic task-selection training than the task-specific algorithm. Transfer of task-selection skills was assessed by having students select a new task in another domain for a fictitious peer student. Results showed that both heuristic and algorithmic training of self-assessment and task-selection skills improved problem-solving posttest performance after a self-regulated learning phase, as well as transfer of task-selection skills. Heuristic training was not more effective for transfer than algorithmic training. These findings show that example-based self-assessment and task-selection training can be an effective and relatively easy to implement method for improving students’ self-regulated learning outcomes. Importantly, our data suggest that the effect on task-selection skills may transfer beyond the trained tasks, although future research should establish whether this also applies when trained students perform novel tasks themselves.     

Is pair programming more effective than other forms of collaboration for young students?

This study investigates differences between collaboration methods in two summer enrichment classes for students entering the sixth grade. In one treatment, students used pair programming. In the other treatment, students engaged in frequent collaboration, but worked ontheir own computer. Students in the two treatments did not differ significantly in their performance on daily quizzes or responses to attitudinal survey questions. However, the students who worked on their own computer completed exercises more quickly than those using pair programming. This study compares two learning environments with high levels of collaboration to isolate aspects of pair programming that are and are not responsible for the reported success of educational research focused on pair programming. This study expands our understanding of pair programming by moving beyond simplistic comparisons of learning environments with and without collaboration and by extending pair programming research to elementary school students.     

What is open learning?

The recent change in this journal's title, from Teaching at a Distance to Open Learning, poses obvious questions of definition. What is open learning? And how does it relate to distance education and adult education? In this article, Roger Lewis, Head of Educational Development Unit at North Staffordshire Polytechnic, makes use of his considerable and varied experience of working with the Open University, the Council for Educational Technology, the Open Tech, the National Extension College and other practitioners of open learning in providing some answers. Readers should find the analytical tools and examples included in the article of considerable use in examining their own experiences in the open learning field.     

How and with what accuracy do children report self-regulated learning in contemporary EFL instructional settings?

European Journal of Psychology of Education - This study aimed to understand how children reflect about learning, report their regulation of learning activity, and develop their performance in...     

Why is letter-name knowledge such a good predictor of learning to read?

The knowledge of letter names measured just before children enter school has been known for a long time as one of the best longitudinal predictors of learning to read in an alphabetic writing system. After a period during which the comprehensive investigation of this relationship was largely disregarded, there is now a growing interest in attempts to understand the role(s) letter names play in literacy acquisition. This paper reviews these recent studies and emphasizes their main findings regarding the influence of letter-name knowledge in early and formal literacy for three main components of literacy acquisition: first, the emergence of the phonological processing of print; then, the learning of letter-sound correspondences; finally, the development of phonemic sensitivity skills. The final section discusses the status of letter-name knowledge (LNK) in literacy acquisition and suggests possible directions for further research.     

Why is the leg shorter than the other？

从三峡大坝的修建，到杨利伟的翱翔太空，中国人一年又一年的期盼得以梦圆。在欣欣向荣的背后，是国家经济实力的不断增强。作为反映国家总体经济实力的核心指标。国内生产总值（GDP）不仅仅是长长的一串数字，更是国家建设的后盾和人民生活水平的保障。我们从GDP数字的变化，不仅可以看到中国前进的步伐，看到改革开放的巨大成就．更可以引发我们很多有益的思考。     

How competent do teachers feel instructing self-regulated learning strategies? Development and validation of the teacher self-efficacy scale to implement self-regulated learning

This study describes the development of a self-report instrument: the Teacher Self-Efficacy Scale to implement Self-Regulated Learning (TSES-SRL). The TSES-SRL assesses teachers' perceived ability of implementing SRL as a specific instructional domain. The process of the item and scale development is presented. Exploratory factor analysis suggests a four-factor structure. Next, confirmatory factor analysis was performed and goodness of fit estimates were calculated, indicating an acceptable fit. Further, comparing the TSES-SRL to The Ohio State Teacher Efficacy Scale reveals the domain-specificity of the instrument. Overall, the TSES-SRL is considered a useful instrument to measure teachers' feelings of competence regarding SRL implementation.     

Learning by writing explanations: Is explaining to a fictitious student more effective than self-explaining?

Research has demonstrated that oral explaining to a fictitious student improves learning. Whether these findings replicate, when students are writing explanations, and whether instructional explaining is more effective than other explaining strategies, such as self-explaining, is unclear. In two experiments, we compared written instructional explaining to written self-explaining, and also included written retrieval and a baseline control condition. In Experiment 1 (N = 147, between-participants-design, laboratory experiment), we obtained no effect of explaining. In Experiment 2 (N = 50, within-participants-design, field-experiment), only self-explaining was more effective than our control conditions for attaining transfer. Self-explaining was more effective than instructional explaining. A cumulating meta-analysis on students’ learning revealed a small effect of instructional explaining on conceptual knowledge (g = 0.22), which was moderated by the modality of explaining (oral explaining > written explaining). These findings indicate that students who write explanations are better off self-explaining than explaining to a fictitious student.     

Self-efficacy and prior domain knowledge: to what extent does monitoring mediate their relationship with hypermedia learning?

While research has documented the key role of monitoring processes during hypermedia learning, limited empirical research has used process data to examine the possibility that these processes mediate the relationship between motivational constructs (such as self-efficacy) and cognitive factors (such as prior domain knowledge) with hypermedia learning outcomes. This multi-method study addressed this issue by examining: (1) The extent to which the relationship between self-efficacy and hypermedia learning outcomes is mediated by the use of specific monitoring processes and; (2) The extent to which the relationship between prior domain knowledge and hypermedia learning outcomes is mediated by the use of specific monitoring processes. Participants included 68 education majors. A self-report questionnaire was used to measure self-efficacy, a pretest was used to measure prior domain knowledge, a posttest was used to measure learning outcomes, and a think-aloud protocol were used to identify the deployment of monitoring processes during a 30-min hypermedia learning task. Results indicated that the relationship between self-efficacy and specific monitoring processes (Monitoring Understanding, Monitoring Environment, and Monitoring Progress Towards Goals) was significantly detectable. Additionally, the relationship between prior domain knowledge and Monitoring Understanding was significantly detectable. Lastly, regression analyses revealed that the relationship between self-efficacy and hypermedia learning outcomes was mediated by the extent to which participants monitored their understanding and the environment.