Self‐report Case‐studies: an experiment in own classroom data collection by teachers

The capacity of Bayesian methods in estimating complex statistical models is undeniable. Bayesian data analysis is seen as having a range of advantages, such as an intuitive probabilistic interpretation of the parameters of interest, the efficient incorporation of prior information to empirical data analysis, model averaging and model selection. As a simplified demonstration, we illustrate (1) how Bayesians test and compare two non‐nested growth curve models using Bayesian estimation with non‐informative prior; (2) how Bayesians model and handle missing outcomes in the context of missing values; and (3) how Bayesians incorporate data‐based evidence from a previous data set, construct informative priors and treat them as extra information while conducting an up‐to‐date analogy analysis.     

A New Way to Teach (or Compute) Pearson's r Without Reliance on Cross‐Products

Many students have difficulty seeing the conceptual ‘link’ between bivariate data displayed in a scatterplot and the statistical summary of the relationship, r. This article shows how to teach (and compute) r such that each datum's ‘direct’ and ‘indirect’ influences are made apparent and used in a new formula for calculating Pearson's r.     

Exploring the nonformal adult educator in twenty-first century contexts using qualitative video data analysis techniques

This study examined how YouTube creates a unique, nonformal cyberspace for Black females to vlog about natural hair. Specifically, we utilized qualitative video data analysis techniques to understand how using YouTube as a facilitation tool has the ability to collectively capture and maintain an audience of more than a million adult learners. After analyzing 30 videos, 4 themes emerged reflective of how using the technology of video assists these nonformal adult educators with regard to: (a) Demystifying Black Natural Hair Myths, (b) Digital Storytelling as an Educational Tool, (c) The Use of Humor, Honesty, and Humility While Facilitating Adults, and (d) The Natural Hair Thing Extends Beyond Cultural Differences. Lastly, we offer implications for future research with regard to the availability and credibility of YouTube as a data source and alternative qualitative video data analysis techniques.     

Psychosocial Status of Adolescents with Learning Disabilities With and Without Comorbid Attention Deficit Hyperactivity Disorder

Some researchers suggest that having a learning disability (LD) may act as a risk factor, increasing the likelihood that adolescents experience more negative outcomes in many areas of their lives. However, researchers have yet to examine in one study how having LD with and without attention deficit hyperactivity disorder (ADHD) is related to a comprehensive set of psychosocial variables across a diverse set of domains (e.g., peer, family, school, intrapersonal). The purpose of the present study was to address that limitation by comparing the perceptions of adolescents with LD (N= 230), with comorbid LD/ADHD (N= 92), and without LD or ADHD (N= 322) regarding their academic orientation, temperament, well‐being, loneliness, parental relationships, victimization, activities, and friendships. Results are consistent with the hypothesis that LD may indeed act as a risk factor increasing the likelihood of more negative outcomes. The results also indicate that for some psychosocial variables this likelihood may be increased in adolescents with comorbid LD/ADHD. The findings have important implications for stakeholders concerned about supporting adolescents with LD with and without comorbid ADHD.     

Book Reviews

We present here a reflexive and critical commentary and exemplification of the teaching and learning of research methodology. The paper focuses on the teaching/learning of qualitative data analysis. It is our belief that it is essential to do data analysis when learning about the process and that there are serious limitations to methodological ‘manuals’ which set out to model the process. In doctoral workshops, Frankham and Stronach have used a passage by Jules Henry to provoke students into generating data which is then analysed as a group. This paper, written with a group of doctoral students, describes the reflexive and iterative processes of data analysis which took place in one such group. We hope that describing our discussions will be of practical use to others in our attempt to iterate a process. Our other purposes include a desire to underline the inappropriacy of the notion of ‘skills’ in the context of research ‘training’ or of following formulaic procedures in interpretive inquiry. Instead the process we set out to illustrate here is embodied and serendipitous and centres on individuals' capacity to think.     

Using the Attribute Hierarchy Method to Make Diagnostic Inferences about Examinees’ Cognitive Skills in Critical Reading

The purpose of this study is to apply the attribute hierarchy method (AHM) to a subset of SAT critical reading items and illustrate how the method can be used to promote cognitive diagnostic inferences. The AHM is a psychometric procedure for classifying examinees’ test item responses into a set of attribute mastery patterns associated with different components from a cognitive model. The study was conducted in two steps. In step 1, three cognitive models were developed by reviewing selected literature in reading comprehension as well as research related to SAT Critical Reading. Then, the cognitive models were validated by having a sample of students think aloud as they solved each item. In step 2, psychometric analyses were conducted on the SAT critical reading cognitive models by evaluating the model‐data fit between the expected and observed response patterns produced from two random samples of 2,000 examinees who wrote the items. The model that provided best data‐model fit was then used to calculate attribute probabilities for 15 examinees to illustrate our diagnostic testing procedure.     

Examining socially shared regulation and shared physiological arousal events with multimodal learning analytics

Socially shared regulation contributes to the success of collaborative learning. However, the assessment of socially shared regulation of learning (SSRL) faces several challenges in the effort to increase the understanding of collaborative learning and support outcomes due to the unobservability of the related cognitive and emotional processes. The recent development of trace-based assessment has enabled innovative opportunities to overcome the problem. Despite the potential of a trace-based approach to study SSRL, there remains a paucity of evidence on how trace-based evidence could be captured and utilised to assess and promote SSRL. This study aims to investigate the assessment of electrodermal activities (EDA) data to understand and support SSRL in collaborative learning, hence enhancing learning outcomes. The data collection involves secondary school students (N = 94) working collaboratively in groups through five science lessons. A multimodal data set of EDA and video data were examined to assess the relationship among shared arousals and interactions for SSRL. The results of this study inform the patterns among students' physiological activities and their SSRL interactions to provide trace-based evidence for an adaptive and maladaptive pattern of collaborative learning. Furthermore, our findings provide evidence about how trace-based data could be utilised to predict learning outcomes in collaborative learning.

Practitioner notes

What is already known about this topic

• Socially shared regulation has been recognised as an essential aspect of collaborative learning success.
• It is challenging to make the processes of learning regulation ‘visible’ to better understand and support student learning, especially in dynamic collaborative settings.
• Multimodal learning analytics are showing promise for being a powerful tool to reveal new insights into the temporal and sequential aspects of regulation in collaborative learning.

What this paper adds

• Utilising multimodal big data analytics to reveal the regulatory patterns of shared physiological arousal events (SPAEs) and regulatory activities in collaborative learning.
• Providing evidence of using multimodal data including physiological signals to indicate trigger events in socially shared regulation.
• Examining the differences of regulatory patterns between successful and less successful collaborative learning sessions.
• Demonstrating the potential use of artificial intelligence (AI) techniques to predict collaborative learning success by examining regulatory patterns.

Implications for practice and/or policy

• Our findings offer insights into how students regulate their learning during collaborative learning, which can be used to design adaptive supports that can foster students' learning regulation.
• This study could encourage researchers and practitioners to consider the methodological development incorporating advanced techniques such as AI machine learning for capturing, processing and analysing multimodal data to examine and support learning regulation.

     

Analytics for learning design: A layered framework and tools

The field of learning design studies how to support teachers in devising suitable activities for their students to learn. The field of learning analytics explores how data about students' interactions can be used to increase the understanding of learning experiences. Despite its clear synergy, there is only limited and fragmented work exploring the active role that data analytics can play in supporting design for learning. This paper builds on previous research to propose a framework (analytics layers for learning design) that articulates three layers of data analytics—learning analytics, design analytics and community analytics—to support informed decision-making in learning design. Additionally, a set of tools and experiences are described to illustrate how the different data analytics perspectives proposed by the framework can support learning design processes.     

(Re)braiding to tell: using trenzas as a metaphorical–analytical tool in qualitative research

Metaphors can be used in qualitative research to illuminate the meanings of participant experiences and examine phenomena from insightful and creative perspectives. The purpose of this paper is to illustrate how I utilized trenzas (braids) as a metaphorical and analytical tool for understanding the experiences and perspectives of Latina teachers around being a well-educated person. Accordingly, this paper is organized into three strands. First, I discuss trenzas as a metaphorical concept in raced–gendered epistemology, highlighting the work of Chicana/Latina feminist scholars in law and education. Second, I describe how metaphorical thinking informed the methodological design. Third, I explain how I used trenzas to make sense of data and build theory. The discussion weaves the three strands together to emphasize the functional and generative nature of trenzas as a metaphorical–analytical tool for gaining critical and nuanced understandings of how personal, professional, and community identities shape participant’ experiences and perspectives.     

Structural Zeros and Their Implications With Log‐Linear Bivariate Presmoothing Under the Internal‐Anchor Design

In equating, when common items are internal and scoring is conducted in terms of the number of correct items, some pairs of total scores (X) and common‐item scores (V) can never be observed in a bivariate distribution of X and V; these pairs are called structural zeros. This simulation study examines how equating results compare for different approaches to handling structural zeros. The study considers four approaches: the no‐smoothing, unique‐common, total‐common, and adjusted total‐common approaches. This study led to four main findings: (1) the total‐common approach generally had the worst results; (2) for relatively small effect sizes, the unique‐common approach generally had the smallest overall error; (3) for relatively large effect sizes, the adjusted total‐common approach generally had the smallest overall error; and, (4) if sole interest focuses on reducing bias only, the adjusted total‐common approach was generally preferable. These results suggest that, when common items are internal and log‐linear bivariate presmoothing is performed, structural zeros should be maintained, even if there is some loss in the moment preservation property.     

Communicating Campus Sexual Assault: A Mixed Methods Rhetorical Analysis

ABSTRACT

This article reports on a mixed methods rhetorical analysis of a data set of news reports on campus sexual assault. A macro-level qualitative analysis of narratives combined with micro-level quantitative content analysis of verb voice offers insight into how news media shapes perceptions of power, blame, and agency in reporting. These findings offer implications for how public actors discuss campus sexual assault and implications for the teaching and practice of research methods in technical communication.     

Makerspace in STEM for girls: a physical space to develop twenty-first-century skills

Makerspace has been lauded as a new way forward to create communities, empower students and bring together enthusiasts of all ages and skill levels “to tinker” and create. Makerspace education has been touted as having the potential to empower young people to become agents of change in their communities. This paper examines how a Makerspace approach can capture the imagination and creativity of female primary school students, and engage them in integrated STEM-based projects. The study scaffolded female tertiary undergraduate students to mentor small groups of girls to complete a project in a STEM Makerspace situated in classrooms. The data generated and analysed from this study were used to determine how Makerspace STEM-based projects were enacted, how they engaged and supported the girls’ learning, and considers the future of a Makerspace approach as a way to progress integrated STEM education.     

Peer Sameness and Peer Diversity: The Influence of Breadth and Depth of Classmates with High Academic Needs in Kindergarten

Research Findings: Relying on a newly released national data set of kindergarten students from the 2010–2011 school year (Early Childhood Longitudinal Study–Kindergarten Class of 2010–2011), the findings suggest that having a greater percentage of same-needs classmates positively boosts both achievement and socioemotional outcomes among kindergartners. However, the overall degree of diversity in the classroom has no effect (either negative or positive) on these same outcomes. Practice or Policy: Alongside changes in schooling integration policies and grade promotion practices, the general education classroom is becoming increasingly diverse academically. It is notable that general education classrooms have been experiencing increases in the presence of children with disabilities and English language learners in addition to increases in the number of retained students. Prior empirical research typically isolated how 1 of these groups with high academic needs might have influenced the outcomes of other students in that same classroom. Rather than focusing on the influence of 1 student group, however, this study adopts a more holistic perspective by examining how the degree of diversity of high-needs classmates in a classroom might be linked to child outcomes.     

Exploring UK secondary teachers' professional values: an overview of the literature since 2000

Background:?Professional commitment from teachers requires more than contractual compliance as personal and professional values are integral to teaching practice. Secondary school teachers are expected to act as role models and demonstrate positive attributes and attitudes in an evolving educational context. Little is known about how they understand or interpret their own values, or realise the shared values that lie at the heart of a school community.

Purpose:?The purpose of this review is to summarise the literature relating to values that teachers hold. The review is concerned with theoretical and empirical studies in which such values are considered, and also any tensions identified between the personal values of teachers and organisational values of the schools reflected in professional practice. This scoping exercise is part of two-year funded empirical research carried out by the authors in five secondary schools in England, using data from individuals, groups and schools on the personal values of teachers and head teachers. This research explored whether these values are congruent with the organisational values schools seek to establish.

Design and methods:?An extensive literature review was undertaken relating to the values held by secondary school professionals. The search was restricted to more recent works (i.e. the year 2000 onwards), and was mainly UK and secondary education focused. The search was conducted using the educational database, Education Indexes on Dialog, and the Electronic Journal Service which is a database covering wider disciplines. To reach harder-to-find research reports, additional strategies were adopted including hand searching of key journals and reference to existing publication lists. The review generated over 1000 published references that were then screened to determine whether publications were based on empirical research conducted in schools, and/or helped a deeper theoretical understanding about the meaning of values.

Conclusion:?The review highlights the integral part values continue to play in education. This article presents a framework of understanding derived from the literary contexts in which values are discussed. There is little empirical data to support current understanding about the values that secondary teachers hold, and how these fit with the organisational values of the schools in which they work. Studies in the context of values and professionalism stress the need for dialogue and reflection so that ‘implicit’ values that teachers hold become explicit, and refined through practice.     

Identifying patterns of students' performance on simulated inquiry tasks using PISA 2015 log-file data

Previous research has demonstrated the potential of examining log-file data from computer-based assessments to understand student interactions with complex inquiry tasks. Rather than solely providing information about what has been achieved or the accuracy of student responses (product data), students' log files offer additional insights into how the responses were produced (process data). In this study, we examined students' log files to detect patterns of students' interactions with computer-based assessment and to determine whether unique characteristics of these interactions emerge as distinct profiles of inquiry performance. Knowledge about the characteristics of these profiles can shed light on why some students are more successful at solving simulated inquiry tasks than others and how to support student understanding of scientific inquiry through computer-based environments. We analyzed the Norwegian PISA 2015 log-file data, science performance as well as background questionnaire (N = 1,222 students) by focusing on two inquiry tasks, which required scientific reasoning skills: coordinating the effects of multiple variables and coordinating theory and evidence. Using a mixture modeling approach, we identified three distinct profiles of students' inquiry performance: strategic, emergent, and disengaged. These profiles revealed different characteristics of students' exploration behavior, inquiry strategy, time-on-task, and item accuracy. Further analyses showed that students' assignment to these profiles varied according to their demographic characteristics (gender, socio-economic status, and language at home), attitudes (enjoyment in science, self-efficacy, and test anxiety), and science achievement. Although students' profiles on the two inquiry tasks were significantly related, we also found some variations in the proportion of students' transitions between profiles. Our study contributes to understanding how students interact with complex simulated inquiry tasks and showcases how log-file data from PISA 2015 can aid this understanding.     

Null Hypothesis Significance Testing and p Values

p values are commonly reported in quantitative research, but are often misunderstood and misinterpreted by research consumers. Our aim in this article is to provide special educators with guidance for appropriately interpreting p values, with the broader goal of improving research consumers’ understanding and interpretation of research findings. Specifically, we discuss null hypothesis significance testing, describe what p values mean and how they are reported, describe some common misconceptions of p values, and provide two examples from the research literature to illustrate how p values are used in the field. Our take‐home message is that p values indicate how likely study results are to occur if the null hypothesis is true, and that p values should be cautiously interpreted.     

Educational performance and attitudes toward school as risk‐protective factors for violence: A study of the Asian/Pacific Islander Youth Violence Prevention Center

The purpose of this study was to examine whether school experiences, school performance, and other risk‐protective factors were related to violence among Hawaiian, Filipino, and Samoan youths residing in Hawai'i. This study analyzed survey data (N = 325) collected in three high schools having concentrations of Filipino, Hawaiian, and Samoan youths, as well as a smaller number of Japanese students, which served as a comparison group. The analyses consisted of bivariate and multivariate analyses of risk protection for violence. Two‐ and three‐way interactions were tested to examine whether there were specific gender and/or ethnic effects. The final model explained 29.3% of the variance in violent behavior. Five variables were significant: grade point average, pressure to choose between school and friends, favorable school attitude, feeling safe, and importance of college. Schools serving these populations should focus on fostering positive bonds between teachers and students and building bridges to families and neighborhoods. © 2010 Wiley Periodicals, Inc.     

Handling Missing Data in the Modeling of Intensive Longitudinal Data

Myriad approaches for handling missing data exist in the literature. However, few studies have investigated the tenability and utility of these approaches when used with intensive longitudinal data. In this study, we compare and illustrate two multiple imputation (MI) approaches for coping with missingness in fitting multivariate time-series models under different missing data mechanisms. They include a full MI approach, in which all dependent variables and covariates are imputed simultaneously, and a partial MI approach, in which missing covariates are imputed with MI, whereas missingness in the dependent variables is handled via full information maximum likelihood estimation. We found that under correctly specified models, partial MI produces the best overall estimation results. We discuss the strengths and limitations of the two MI approaches, and demonstrate their use with an empirical data set in which children’s influences on parental conflicts are modeled as covariates over the course of 15 days (Schermerhorn, Chow, & Cummings, 2010).     

综合实训课程中表格控件的使用方法和技巧

通过对综合课程中常用表格控件的介绍,详细地阐述了如何运用表格控件生成程序需要的数据清单,如何快速建立基于表格控件的数据浏览表单和用表格控件显示多数据源和显示虚拟字段,并且探讨了表格控件使用过程中常见问题的解决方法和技巧。