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If students are to be successful in school, at work, and in their personal lives, they must learn to write. This requires that they receive adequate practice and instruction in writing, as this complex skill does not devebp naturally. A basic goal of schooling then is to teach students to use this versatile tool effectively and flexibly. Many schools across the world do not achieve this objective, as an inordinate number of students do not acquire the writing skills needed for success in society today. One reason why this is the case is that many students do not receive the writing instruction they need or deserve. This chapter identifies factors that inhibit good writing instruction, including instructional time; teachers' preparation and beliefs about writing; national, state, district, and school policies; and historical, social, cultural, and political influences. It then examines how we can address these factors and change classroom writing practices for the better across the world by increasing pertinent stakeholders' knowledge about writing, with the goal ofdevebping and actualizing visions for writing instruction at the policy, school, and classroom levels. This includes specific recommendations for helping politicians, school administrators, teachers, and the public acquire the needed know-how to make this a reality.

Every day, students and instructors are faced with the decision of when to study information. The timing of study, and how it affects memory retention, has been explored for many years in research on human learning. This research has shown that performance on final tests of learning is improved if multiple study sessions are separated—i.e., \"spaced\" apart—in time rather than massed in immediate succession. In this article, we review research findings of the types of learning that benefit from spaced study, demonstrations of these benefits in educational settings, and recent research on the time intervals during which spaced study should occur in order to maximize memory retention. We conclude with a list of recommendations on how spacing might be incorporated into everyday instruction.

Depletion of limited working memory resources may occur following extensive mental effort resulting in decreased performance compared to conditions requiring less extensive mental effort. This \"depletion effect\" can be incorporated into cognitive load theory that is concerned with using the properties of human cognitive architecture, especially working memory, when designing instruction. Two experiments were carried out on the spacing effect that occurs when learning that is spaced by temporal gaps between learning episodes is superior to identical, massed learning with no gaps between learning episodes. Using primary school students learning mathematics, it was found that students obtained lower scores on a working memory capacity test (Experiments 1 and 2) and higher ratings of cognitive load (Experiment 2) after massed than after spaced practice. The reduction in working memory capacity may be attributed to working memory resource depletion following the relatively prolonged mental effort associated with massed compared to spaced practice. An expansion of cognitive load theory to incorporate working memory resource depletion along with instructional design implications, including the spacing effect, is discussed.

The segmenting effect states that people learn better when multimedia instructions are presented in (meaningful and coherent) learner-paced segments, rather than as continuous units. This meta-analysis contains 56 investigations including 88 pairwise comparisons and reveals a significant segmenting effect with small to medium effects for retention and transfer performance. Segmentation also reduces the overall cognitive load and increases learning time. These four effects are confirmed for a system-paced segmentation. The meta-analysis tests different explanations for the segmenting effect that concern facilitating chunking and structuring due to segmenting the multimedia instruction by the instructional designer, providing more time for processing the instruction and allowing the learners to adapt the presentation pace to their individual needs. Moderation analyses indicate that learners with high prior knowledge benefitted more from segmenting instructional material than learners with no or low prior knowledge in terms of retention performance.

Spaced and interleaved practices have been identified as effective learning strategies which sometimes are conflated as a single strategy and at other times treated as distinct. Learning sessions in which studying information or practicing problems are spaced in time with rest-from-deliberate-learning periods between sessions generally result in better learning outcomes than massed practice without rest-from-deliberate-learning periods. Interleaved practice also consists of spaced sessions, but by interleaving topics rather than having rest-from-deliberate-learning periods. Interleaving is usually contrasted with blocking in which each learning topic is taught in a single block that provides an example of massed practice. The general finding that interleaved practice is more effective for learning than blocked practice is sometimes attributed to spacing. In the current paper, the presence of rest-from-deliberate-learning periods is used to distinguish between spaced and interleaved practice. We suggest that spaced practice is a cognitive load effect that can be explained by working memory resource depletion during cognitive effort with recovery during rest-from-deliberate-learning, while interleaved practice can be explained by the discriminative-contrast hypothesis positing that interleaving assists learners to discriminate between topic areas. A systematic review of the literature provides evidence for this suggestion.

There are many claims that gamification (i.e., using game elements outside games) impact decreases over time (i.e., the novelty effect). Most studies analyzing this effect focused on extrinsic game elements, while fictional and collaborative competition have been recently recommended. Additionally, to the best of our knowledge, no long-term research has been carried out with STEM learners from introductory programming courses (CS1), a context that demands encouraging practice and mitigating motivation throughout the semester. Therefore, the main goal of this work is to better understand how the impact of a gamification design, featuring fictional and competitive-collaborative elements, changes over a 14-week period of time, when applied to CS1 courses taken by STEM students (N = 756). In an ecological setting, we followed a 2x7 quasi-experimental design, where Brazilian STEM students completed assignments in either a gamified or non-gamified version of the same system, which provided the measures (number of attempts, usage time, and system access) to assess user behavior at seven points in time. Results indicate changes in gamification’s impact that appear to follow a U-shaped pattern. Supporting the novelty effect, the gamification’s effect started to decrease after four weeks, decrease that lasted between two to six weeks. Interestingly, the gamification’s impact shifted to an uptrend between six and 10 weeks after the start of the intervention, partially recovering its contribution naturally. Thus, we found empirical evidence supporting that gamification likely suffers from the novelty effect, but also benefits from the familiarization effect, which contributes to an overall positive impact on students. These findings may provide some guidelines to inform practitioners about how long the initial contributions of gamification last, and how long they take to recover after some reduction in benefits. It can also help researchers to realize when to apply/evaluate interventions that use gamification by taking into consideration the novelty effect and, thereby, better understand the real impact of gamification on students’ behavior in the long run.

Studies examining decontextualized associative vocabulary learning have shown that long spacing between encounters with an item facilitates learning more than short or no spacing, a phenomenon known as distributed practice effect. However, the effect of spacing on learning words in context is less researched and the results, so far, are inconsistent. In this study, we compared the effect of massed and spaced distributions on second language vocabulary learning from reading. Japanese speakers of English encountered 48 novel vocabulary items embedded in informative English sentences, inferred their meanings from contexts, and received feedback in the form of English synonyms and Japanese translation equivalents. To test the hypothesis that the effects of spacing might differentially affect the development of explicit or tacit word knowledge, spacing effects were measured using semantic priming as well as a meaning recall and a meaning–form matching posttest. Results showed an advantage of spaced over massed learning on the meaning recall and meaning–form matching posttests. However, a similar semantic priming effect was observed irrespective of whether an item was encountered in the massed or spaced distribution. These results suggest that the spacing effect holds in contextual word learning for the development of explicit vocabulary knowledge, but massing appears to be as effective as spacing for the acquisition of tacit semantic knowledge.

Policy and practice have charged forward with emphasizing the necessity to reduce school absenteeism in the fall (i.e., Attendance Awareness Month). However, no empirical basis served to bolster these efforts. This study examined whether fall versus spring absenteeism was linked to spring state exam scores for a sample of elementary students over 3 years. Using district data, the findings suggested spring absences were associated with lower testing performance, with the most critical period being the 30-day window leading up to the test. This study illustrates that most is at stake for student test performance by missing school in the days and months leading up to the test date and that different support systems are needed to address subgroups of students.

Prediction of student performance is one of the most important subjects of educational data mining. Artificial neural networks are seen to be an effective tool in predicting student performance in e-learning environments. In the studies carried out with artificial neural networks, performance predictions based on student scores are generally made, but students’ use of learning management system is not focused. In this study, performances of 3518 university students, who studying and actively participating in a learning management system, were tried to be predicted by artificial neural networks in terms of gender, content score, time spent on the content, number of entries to content, homework score, number of attendance to live sessions, total time spent in live sessions, number of attendance to archived courses and total time spent in archived courses variables. Since it is difficult to interpret how much input variables in artificial neural networks contribute to predicting output variables, these networks are called black boxes. Also, in this study the amount of contribution of input variables on the prediction of output variable was also examined. The artificial neural network created as a result of the study makes a prediction with an accuracy of 80.47%. Finally, it was found that the variables of number of attendance to the live classes, the number of attendance to archived courses and the time spent in the content contributed most to the prediction of the output variable.

This longitudinal study explored the roles of item- and learner-related variables in L2 learners’ development of productive collocation knowledge (L1 = Dutch; L2 = German; NLearners= 50). Learners’ form recall knowledge of 35 target collocations was measured three times over a 3-year period. The item-related variables investigated were L1-L2 congruency, corpus frequency, association strength, and imageability. We also explored the learner-related variables L2 prior productive vocabulary knowledge and L2 immersion. Mixed-effects regression modeling indicated a significant effect of time, congruency, and prior productive vocabulary knowledge on learners’ collocation learning. While learners’ knowledge of congruent collocations remained relatively stable after year one, knowledge of incongruent collocations increased significantly. Learners’ prior productive vocabulary knowledge was clearly associated with growth of productive collocation knowledge, but besides overall growth there were instances of attrition.