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Due to repeated observations of an outcome behavior in N-of-1 or single-case design (SCD) intervention studies, the occurrence of missing scores is inevitable in such studies. Approximately 21% of SCD articles published in five reputable journals between 2015 and 2019 exhibited evidence of missing scores. Missing rates varied by designs, with the highest rate (24%) found in multiple baseline/probe designs. Missing scores cause difficulties in data analysis. And inappropriate treatments of missing scores lead to consequences that threaten internal validity and weaken generalizability of intervention effects reported in SCD research. In this paper, we comprehensively review nine methods for treating missing SCD data: the available data method, six single imputations, and two model-based methods. The strengths, weaknesses, assumptions, and examples of these methods are summarized. The available data method and three single imputation methods are further demonstrated in assessing an intervention effect at the class and students' levels. Assessment results are interpreted in terms of effect sizes, statistical significances, and visual analysis of data. Differences in results among the four methods are noted and discussed. The extensive review of problems caused by missing scores and possible treatments should empower researchers and practitioners to account for missing scores effectively and to support evidence-based interventions vigorously. The paper concludes with a discussion of contingencies for implementing the nine methods and practical strategies for managing missing scores in single-case intervention studies.

With new technology tools available for educators and students, effectively using these tools to improve teaching and learning has become a constant theme for research and practice in the field of education. In this study, case-analysis was conducted on 305 published studies (from 140 peer-reviewed regional, national and international journals) that explored the effect of using technology on student learning in science, mathematics, and engineering (SME) at K-12 and university levels. Seven factors were summarized ("Content Design," "Technology Design," "Integration Design," "Interactive Learning," "Motivation," "New Trends in Content," and "New Trends in Technology") and used to generate a logistic predictive model. The model suggests that five of the seven factors significantly predicting the probability of a technology-based SME learning experience to be successful. A technology integration model was tested with the case analysis. Static and dynamic instructional design models and new trends in e-learning are also discussed.

This qualitative-dominant mixed methods study aimed to investigate how native English speaking third graders (n = 72) and sixth graders (n = 88) navigate cohesive ties in academic sentences. There are studies on supporting students with academic language at the word and text levels, but less research has been done on readers’ knowledge of the dense and challenging sentences in academic texts. The current study examines both how students navigate cohesion in academic sentences as well as how their knowledge of cohesion relates to their performance on reading comprehension measures. With a multi-case study framework, we analyzed students’ (n = 6) metalinguistic interviews with academic sentences. We then designed Maze tasks for a larger sample (n = 160) to identify patterns in students’ knowledge of cohesion. We also conducted correlational analyses between students’ sentence-level knowledge and performance on measures of reading comprehension. Qualitative findings suggest that students draw on both metalinguistic and epilinguistic knowledge to explain cohesion, and that students value explicit instruction with academic sentences. Quantitative findings show that knowledge of cohesive ties is significantly correlated with performance on reading comprehension measures. Implications and future research for both monolingual and multilingual learners are addressed.

In educational technology research, most studies are conducted to explore the effectiveness of using technology to improve teaching and learning. Priori power analysis enables researchers to determine sufficient sample size for achieving adequate statistical power during research planning. Observed power analysis is carried out on completed studies to estimate statistical power. While priori power analysis is recommended for sample size estimation, observed power analysis has been criticized for being incorrect and misleading. To understand current practices of power analysis in the field, we conducted a content analysis on five years' publications in "Educational Technology Research and Development" from 2014 to 2018, a total of 178 articles. Our findings showed that only two articles (1.1%) reported a priori power analysis and seven articles (4.0%) reported observed power although it is not recommended. To facilitate sample size determination during research planning, we generated sample size tables for various t tests and ANOVAs from G*Power. Best practice recommendations to conduct and report educational technology research are provided.

Teachers have faced various challenges during the coronavirus pandemic, including lack of skills and knowledge to teach remotely, unstable or no internet access for students in rural areas, and increasing needs to stimulate student motivation. In this article, we introduce the design, development, and implementation of a stand-alone package of multilayer videos that can be delivered to learners with or without internet access. The multilayer videos simulate real classroom environments and learning experiences to facilitate remote learning, and consist of three layers: session guidance videos (Layer 1), content instructional videos (Layer 2), and activity videos (Layer 3). The session guidance videos provide students with a road map of the class session. The content instructional videos are designed to introduce the course content. The activity videos are developed to enhance hands-on learning activities. A case study was conducted in which we used such multilayer videos to teach right triangle trigonometry. Preliminary results from the case study showed that most students gained knowledge from watching the videos. In addition, students gave positive written feedback on the multilayer videos. However, they still preferred the conventional in-person learning approach to the multilayer video learning approach. We provide our suggestions on designing multilayer videos to enhance remote learning.

There are only a handful of studies focused on assessing online teaching. Yet, the uniqueness of online course environment provides instructors more opportunities to conduct self-assessment of their own teaching than the traditional face-to-face classroom. In this paper, we demonstrate two types of self-assessment through two cases that online course instructors can use to evaluate the course content during their regular online instructional procedures. An end-of-semester oral examination was used in Case One whereas the weekly discussion posts were used in Case Two. The instructors performed self-assessment, based on which they redesigned the course contents and activities. Nonparametric analyses were used to examine students' learning outcomes. Results indicate that, in both cases, student learning improved with the redesigned contents and activities.

Literature has suggested numerous benefits of online learning. In this study, we focused on asynchronous online discussion in higher education. We defined effective online discussions as making social presence known and conducting multidimensional discussions. Three dimensions were used to define multidimensional discussions: time, learning space, and example. Discussion posts and course evaluations made by graduate students in two online courses were examined to understand whether different sizes of online discussion groups and requirements for discussions can generate different frequencies of social presence and multidimensional discussions. Results showed that when the class size was around 30, whole class interaction in online discussions and requiring students to reply to others' posts encouraged students to make their social presence known and to conduct multidimensional discussions. Furthermore, when students were assigned to small groups of three or four students for online discussions, the frequencies of social presence and multidimensional discussions depended on other group members' engagement in discussions. Findings from the study also provided evidence that making one's social presence known was positively related to multidimensional discussions. Implications of the findings are discussed.

Homeless children usually experience high mobility. Yet, it is not clear if the degree of mobility among homeless children is associated with their academic performance. Furthermore, an emerging body of literature is beginning to examine the impact of specific living arrangements (e.g., living with families or friends) on homeless family and child outcomes. This research aimed to examine the effects of demographic risk factors, as well as mobility and type of living arrangement, on the academic performance of homeless children receiving educational support through the McKinney-Vento Act. Although neither mobility or living arrangement were associated with standardized test achievement, minority status, gender, special learning needs, and absenteeism still presented as risk factors for academic achievement in this sample of children experiencing homelessness. Recommendations for teacher practices and classroom instructions are presented.

Given the long history of discussion of issues surrounding statistical testing and effect size indices and various attempts by the American Psychological Association and by the American Educational Research Association to encourage the reporting of effect size, most journals in education and psychology have witnessed an increase in effect size reporting since 1999. Yet, effect size was often reported in three indices, namely, the unadjusted "R"[superscript 2], Cohen's "d", and "?"[superscript 2] with a simple labeling of small, medium, or large, according to Cohen's (1969) criteria. In this article, the authors present several alternatives to Cohen's "d" to help researchers conceptualize effect size beyond standardized mean differences for between-subject designs with two groups. The alternative effect size estimators are organized into a typology and are empirically contrasted with Cohen's "d" in terms of purposes, usages, statistical properties, interpretability, and the potential for meta-analysis. Several sound alternatives are identified to supplement the reporting of Cohen's "d." The article concludes with a discussion of the choice of standardizers, the importance of assumptions, and the possibility of extending sound alternative effect size indices to other research contexts.

The experiment was to explore the effect of fermented feed on growth performance and gut microbiota of Cipangopaludina cahayensis. A total of 60 Cipangopaludina cahayensis with an average weight of 25 g were selected and randomly divided into two groups, with three replicates in each group and 10 Cipangopaludina cahayensis in each replicate. Group A and group B was fed with basic feed and fermented basic feed, respectively. The experimental period was 20 d. At the end of the experiment, the intestinal content of snails were taken, detected the intestinal flora diversity by 16S rDNA high-throughput sequencing technology. The results showed that the survival rates of both groups of Cipangopaludina cahayensis were 100%. Compared with group A, the WGR, SGR, and PER of group B were all increased, feed coefficient was reduced ( P>0.05). A total of 375 141 effective sequences were obtained by highthroughput sequencing, with the sequence length ranging from 416~455 bp. Clustering and partitioning effective sequences, and conducting OTU statistics, it was found that OTU coverage rate of each group of samples was above 99.9%. In group A and group B, the first six bacterial phyla with the highest abundance in two groups were Proteobacteria, Bacteroides, Planctomycetes, Acidobacteria, Actinomyces and Chloroflexi. At the phylum classification level. In group A and group B, the top 5 genera were Proteobacteria, Bacteroidetes, Firmicutes, Softicutes, and Chlamydia. Compare with group A, the relative abundance of the top 5 genera in group B was increased, with Firmicutes and Chlamydia significantly increased ( P<0.05). The number of OTU, Chao1 index and Simpson index of group B were higher than those of group A. The study indicates that fermented feed can enhance the diversity and abundance of the gut microbiota community of Cipangopaludina cahayensis. [ABSTRACT FROM AUTHOR]