The Effects of Data-based Instruction (DBI) for Students with Learning Difficulties in Korea: A Single-subject Meta-analysis

Data-based instruction (DBI) is an ongoing process to utilize students’ data for determining when and how to intensify intervention. It is an educational approach that is suggested as effective to enhance achievements of struggling learners, particularly for those who did not respond to intensive intervention in usual ways. In Korea, DBI was introduced and applied for students with learning difficulties especially since 2000 when the first Korea curriculum-based measurement (CBM) was developed as the name of Basic Academic Skills Assessment. Despite a number of studies accumulated since then, there has been a lack of research that examined the level of evidence-based practice (EBP) of DBI research. Thus, the present study sought to synthesize the DBI research so far in Korea by analyzing the effectiveness of DBI for school-aged students with learning difficulties via meta-analysis and evaluating the quality of the research. In this study, a total of 32 single-subject design studies were used. Multilevel meta-analysis revealed that the mean effect size of DBI was statistically significant (B = 1.34) and there was significant variance across participants in effect sizes. The results from the conditional model showed that exceptionality type, the number of sessions, and the length of each session were significantly accountable for the variability of effect sizes. In addition, the results of the qualitative analysis revealed the acceptable quality of the overall DBI research with some limitations. Based on these findings, implications and study limitations were discussed.

Struggling Learners' Achievement Level Using Electronic Strategic Intervention Material In Mathematics (ESIMATH)

This study focused on the achievement levels of Grade 11 struggling learners using an electronic Strategic Intervention Material in Mathematics (eSIMath) in teaching least mastered competencies in the subject, Statistics and Probability for Senior High School. A Solomon four-group quasi-experimental research design was employed to two classes using eSIMath-based instruction, and two classes via conventional instruction, who were identified through a local diagnostic examination given by the teacher-researcher before the instruction for the second semester of the school year 2019-2020. The data gathered were analyzed using independent and dependent t-test, Dunnett's T3 test for post-hoc analysis of posttest scores, and assessment of mean gained scores. Findings of the study showed that the use of eSIMath-based instruction is an effective approach in the increase of struggling learners' achievement level in Statistics & Probability.

A new approach to identify dropout learners based on their performance-based behavior

Distance learning environments are increasingly offering more comfort to both learners and teachers, allowing them to carry out their academic tasks remotely, especially in critical times where it is difficult, or even dangerous, to bring these actors together in one physical place. Nevertheless, These same environments are complaining about the massive dropout numbers among their learners. Therefore, designing new intelligent systems capable of reducing these numbers becomes imperative. This paper proposes a new approach capable of identifying and assisting endangered learners experiencing difficulties by monitoring and analyzing their behavior inside the e-learning environment. By building dynamic models to follow the learners’ current situation, the proposed approach could intervene autonomously to save learners identified as struggling. Relying on distributed artificial intelligence instead of humans to closely monitor learners within distance learning environments can be very effective when identifying struggling learners. Furthermore, targeting these learners with early enough and carefully designed interventions can reduce the number of dropouts.

Cognition, Behaviour, and Mental Health in Struggling Learners: A Spotlight on Girls

Objectives: Fewer girls than boys are identified as struggling at school. The objectives of this study were to: i) identify dimensions of cognition, behaviour and mental health in a unique transdiagnostic sample of struggling learners; ii) test whether these constructs were equivalent for boys and girls, and; iii) compare their performance across the dimensions. Methods: 805 school-aged children, identified by practitioners as experiencing problems in cognition and learning, completed cognitive assessments, and parents/carers rated their behaviour and mental health problems. Results: Three cognitive, three behavioural, and two mental health dimensions distinguished the sample. Dimensions were structurally comparable between boys and girls, but differences in severity were present: girls had greater cognitive impairments; boys had more severe externalising problems. Conclusions: Gender biases to stereotypically male behaviours are prevalent among practitioners, even when the focus is on identifying cognitive and learning difficulties. This underscores the need to include cognitive and female-representative criteria in diagnostic systems to identify girls whose difficulties could go easily undetected.

Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners

Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain–behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5–18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role ‘between’ brain and behavior. We discuss implications and possible avenues for future studies.

Challenges of Urban Educators in Implementing State Standards for Students with Disabilities

A lack of information, research, and teacher training exists on the effective implementation of Common Core State Standards (CCSS) or other state standards for struggling learners. The pace and standardization of the curriculum are often at odds with the unique learning needs of students from diverse backgrounds. Researchers in one large urban school district conducted a series of focus groups with special educators to identify their perceptions of these standards and the training needs associated with effective implementation of the standards. The results revealed a pressing need for professional development to facilitate effective implementation of the standards for struggling learners in urban settings. Implications for teacher preparation and urban education are discussed.

Shedding light on autistic traits in struggling learners: A blind spot in medical education

Some highly challenging, seemingly “unsolvable” situations that arise in medical education could be the result of autistic traits (AT) in learners. AT exist in physicians and learners, ranging from profiles compatible with DSM-5’s criteria for autism spectrum disorder (ASD) to more subtle manifestations of ASD’s “broader phenotype.” Often associated with strengths and talents, AT may nonetheless pose significant challenges for learning, teaching, and practising medicine. Since AT remain widely under-recognized and misunderstood by educators, clinicians, and affected individuals alike, they represent a blind spot in medical education. The use of a “neurodiversity lens” to examine challenging situations may help educators consider different pedagogical approaches to address those potentially stemming from AT.This paper aims to raise awareness and understanding of AT-related difficulties in struggling medical learners. To overcome the blind spot challenge and help develop this “neurodiversity lens,” we explore different angles. Beyond any diagnostic consideration, we offer a series of contextual examples, paralleled with explanatory concepts from the field of ASD. We also underline the role of context on functional impact and describe the often ill-defined pattern of challenges encountered, as well as the fertile grounds for interpersonal misunderstandings and disrespect. We propose historical, cultural, and clinical reasons likely contributing to the blind spot. Mindful of the potential risks of prejudice associated with identifying AT-related difficulties, we underline the necessity and feasibility of conciliating diversity and dignity with accountability standards for medical competence.

Use of Cognitive Apprenticeship Models of Instruction to Support Middle School Students’ Construction and Critique of Written Scientific Explanations and Arguments

Writing in science can be challenging for secondary students, particularly for those with learning disabilities, students who are English learners (EL), and students who struggle with literacy due to other cognitive, language-based, or motivational learning difficulties (i.e., at risk or struggling learners). Moreover, science teachers are generally not equipped to support students’ writing in ways that are authentic to science. Despite being described more than 30 years ago, the field lacks information on cognitive apprenticeships that focus on disciplinary literacy, especially in science. In this paper, we take up these challenges and describe two intervention programs with middle school teachers and their students, focusing on the scientific practices of explanation and argumentation. We describe efforts to support students’ written construction and critique of explanations and arguments, and suggest ways that general and special educators can support students’ engagement in scientific practices through writing.