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In this article, we analyze the relationship between class sizes and examination results in higher education. Data from the University of Stavanger, collected in the Common Student System (FS) in the period from 2011 to 2021, shows that there is a negative correlation between the number of students enrolled on courses and examination results. An increase in the number of students taking a course reduces the average scores. We also show that the difference in examination results for different class sizes decreases when the course level increases. [ABSTRACT FROM AUTHOR]

Turtle species in the Family Podocnemididae, including the Colombian endemic and critically endangered Magdalena River Turtle Podocnemis lewyana, characteristically present low recapture rates that preclude estimation of population parameters using maximum likelihood modeling. In our 12-year monitoring project with this species, we evaluated changes in relative abundances, proportions of sex/size classes, and individual body sizes and body conditions in a population in four channels in the middle Magdalena River drainage. We also inspected for associations between trends in changes in these variables and differences in hunting pressure and habitat degradation. To inspect for temporal and spatial demographic dynamics, we estimated variation in relative abundances using the Catch Per Unit Effort index, the total number of turtles captured over an entire 5-day sampling period using ten baited funnel traps. Relative abundances and the proportions of sex/size classes were different between sites and years. We found a significant decline in the proportion of females and juveniles over time, along with evidence that the females still present were smaller in body size. Our results support the hypothesis that hunting eliminates adult females from these sites, perhaps also translating into a reduction in recruitment. The lack of evidence of generalized declines in body condition of all size classes suggests that habitat degradation might contribute less to the population declines in this region. Our results also illustrate that even when recapture rates are low, monitoring turtles via standardized trapping may yield insights into the population's conservation status that other relative abundance indices cannot. [ABSTRACT FROM AUTHOR]

The imbalance in student-teacher ratio and the diversity of student population pose challenges to MOOC's quality of instructor support. An understanding of student profiles, such as who they are and how they behave, is critical to improving personalized support of MOOC learning environments. While past studies have explored different types of student profiles, few have been done to investigate which student profiles lead to successful performance and what behavior patterns are exhibited by successful and unsuccessful performance groups. To address this research gap, we employed both bottom-up and top-down strategies, to gain useful insights into student learning in the context of MOOCs. From learning behavior records of 26,862 students in six MOOCs, we identified and validated three behavior attributes: effort regulation, self-assessment, and learner participation. Our results revealed that effort regulation emerged as the foremost important factor that positively contributes to students' academic performance in MOOCs. Particularly, online persistence was the strongest positive predictor impacting student success. Based on the behavior attributes ascertained, we demonstrated five student sub-profiles with different behavior patterns: Persistence Achievers and Social Collaborators in the successful group; Dabblers, Disengagers, and Slackers in the unsuccessful group. Our analysis revealed that successful performers engaged with the course in quite different ways. We also investigated how effort regulation differed significantly between successful and unsuccessful performers. Unexpectedly, we also noticed that Persistence Achievers, despite their success, exhibited a high degree of procrastination. This work offers novel insights into instructional interventions for supporting MOOC learning. [ABSTRACT FROM AUTHOR]

The objective of this research was to identify the prevalence of voice disorders among teachers in the Kathmandu District of Nepal, with an emphasis on identifying possible risk factors that may be associated with these disorders. A cross-sectional study design was used, with both quantitative and qualitative data-gathering techniques using a mixed-methods approach. Data were collected from 95 non-teachers and 194 participating teachers from different schools in Kathmandu Valley. The analysis covered self-reported voice problem prevalence, job details, and demographic data. We examined the relationships between several variables and voice issues, including gender, class size, length of instruction, and tobacco usage. Findings: Compared with nonteachers (33.7%), teachers had a considerably greater prevalence of voice issues (69.1%). Greater class size and more than ten years of teaching experience were shown to be risk factors, while female instructors reported a greater prevalence of voice issues. Additionally, it was shown that instructors' voice issues are also linked to tobacco usage. The results of this study highlight how critical it is to provide voice therapy to educators employed in the Kathmandu District, particularly those in at-risk categories such as female instructors, more experienced educators, and educators with larger class sizes. The outcomes demonstrated important impacts on teacher well-being, job satisfaction, and academic achievement. More research and intervention strategies are needed to minimize the effects of voice problems and promote a positive teaching and learning environment. [ABSTRACT FROM AUTHOR]

The use of Experience Sampling Methods (ESM) to assess students' experiences, motivation, and emotions by sending signals to students at random or fixed time points has grown due to recent technological advances. Such methods offer several advantages, such as capturing the construct in the moment (i.e., when the events are fresh on respondents' minds) or providing a better understanding of the temporal and dynamic nature of the construct, and are often considered to be more valid than retrospective self-reports. This article investigates the validity and reliability of a variant of the ESM, the DEBE (an acronym for difficult, easy, boring and engaging, and pronounced 'Debbie') feedback, which captures student-driven (as and when the student wants to report) momentary self-reports of cognitive-affective states during a lecture. The DEBE feedback is collected through four buttons on mobile phones/laptops used by students. We collected DEBE feedback from several video lectures (N = 722, 8 lectures) in different courses and examined the threats to validity and reliability. Our analysis revealed variables such as student motivation, learning strategies, academic performance, and prior knowledge did not affect the feedback-giving behavior. Monte Carlo simulations showed that for a class size of 50 to 120, on average, 30 students can provide representative and actionable feedback, and the feedback was tolerant up to 20% of the students giving erroneous or biased feedback. The article discusses in detail the aforementioned and other validity and reliability threats that need to be considered when working with such data. These findings, although specific to the DEBE feedback, are intended to supplement the momentary self-report literature, and the study is expected to provide a roadmap for establishing validity and reliability of such novel data types. [ABSTRACT FROM AUTHOR]

Writing essays is an important skill which enables one to clearly write the ideas and understanding of certain topic with the help of language articulation and examples. Writing essay is a skill so is the grading of those essays. It requires a lot of efforts to grade these essays and the task becomes tedious and repetitive when the student to teacher ratio is high. As with any other repetitive task, the intervention of technology for automated essay grading has been thought of long back. However, the main challenge in automated essay grading lies in the understanding of language construction, word usage and presentation of idea/ argument/ narration. Language complexity makes natural language understanding a challenging task. In this work, we show our experiments with pre-trained static word embeddings like GloVe, fastText and pre-trained contextual model Bidirectional Encoder Representations from Transformers (BERT) for the task of automated essay grading. For the regression task, we have used Long Short-Term Memory (LSTM) and Support Vector Regression (SVR) models under various feature settings framed from the learnt embeddings. The results are shown with the ASAP-AES dataset on all 8 prompts. Our work shows average Quadratic Weighted Kappa (QWK) of 0.81 and 0.71 with SVR and LSTM on in-domain test set essays, respectively. The SVR model shows a better QWK than the human-human agreement of 0.75. To the best of our knowledge, our SVR model with pre-trained BERT embeddings achieve the highest average QWK reported on ASAP-AES data set. We further show the performance of our approach with adversary samples generated using permuted essays and off-topic essays. We experimentally show that our LSTM model though does not show high QWK score with human assigned grade but is robust against the adversarial settings considered. [ABSTRACT FROM AUTHOR]

Refactoring is a maintenance task that aims at enhancing the quality of a software's source code by restructuring it without affecting the external behavior. Move method refactoring (MMR) involves reallocating a method by moving it from one class to the class in which the method is used most. Several studies have been performed to explore the impact of MMR on several quality attributes. However, these studies have several limitations related to the applied approaches, considered quality attributes, and size of the selected datasets. This paper reports an empirical study that applies statistical and machine learning (ML) approaches to explore the impact of MMR on code quality. The study overcame the limitations of the existing studies, and this improvement is expected to make the results of this study more reliable and trustworthy. We considered eight quality attributes and thirty quality measures, and a total of approximately 4 K classes from seven Java open-source systems were involved in the study. The results provide evidence that most of the quality attributes were significantly improved by MMR in most cases. In addition, the results show that a limited number of measures, when considered individually, have a significant ability to predict MMR, whereas most of the considered measures, when considered together, significantly contribute to the MMR prediction model. The constructed ML-based prediction model has an area under curve (AUC) value of 96.6%. [ABSTRACT FROM AUTHOR]

The educational benefit of the traditional didactic lecture to learners in Higher Education is hotly debated. Given increasing student numbers, existing technical set ups and many logistical concerns, lectures remain the norm in many Higher Education Institutions (HEIs). In this personal view piece, we discuss the benefits, opportunities, and challenges of incorporating dynamic teaching approaches, including "draw-alongs" and animations into undergraduate lectures, typically with large class sizes, to create more engaging and interactive lectures for learners. [ABSTRACT FROM AUTHOR]

This paper aims to improve the methodology and results accuracy of MEDALUS model for assessing land degradation sensitivity through the application of different data detail levels and by introducing the application of Ellenberg indices in metrics related to vegetation drought sensitivity assessment. For that purpose, the MEDALUS model was applied at 2 levels of detail. Level I (municipality level) implied the use of available large-scale databases and level II (watershed) contains more detailed information about vegetation used in the calculation of the VQI and MQI factors (Fig. S6). The comparison was made using data based on CORINE Land Cover (2012) and forest inventory data, complemented with object-based classification. Results showed that data based on forest inventory data with the application of Ellenberg's indices and object-based classification have one class more, critical (C1 and C2) and that the percentage distribution of classes is different in both quantitative (area size of class sensitivity) and qualitative (aggregation and dispersion of sensitivity classes). The use of data from Forest Management Plans and the application of Ellenberg's indices affect the quality of the results and find its application in the model, especially if these results are used for monitoring and land area management on fine scales. Remote sensed data images (Sentinel-2B) were introduced into the methodology as a very important environmental monitoring tool and model results validation. [ABSTRACT FROM AUTHOR]

In curriculum learning the order of concepts is determined by the teacher but not the examples for each concept, while in machine teaching it is the examples that are chosen by the teacher to minimise the learning effort, though the concepts are taught in isolation. Curriculum teaching is the natural combination of both, where both concept order and the set of examples can be chosen to minimise the size of the whole teaching session. Yet, this simultaneous minimisation of teaching sets and concept order is computationally challenging, facing issues such as the "interposition" phenomenon: previous knowledge may be counter-productive. We build on a machine-teaching framework based on simplicity priors that can achieve short teaching sizes for large classes of languages. Given a set of concepts, we identify an inequality relating the sizes of example sets and concept descriptions. This leverages the definition of admissible heuristics for A* search to spot the optimal curricula by avoiding interposition, being able to find the shortest teaching sessions in a more efficient way than an exhaustive search and with the guarantees we do not have with a greedy algorithm. We illustrate these theoretical findings through case studies in a drawing domain, polygonal strokes on a grid described by a simple language implementing compositionality and recursion. [ABSTRACT FROM AUTHOR]

This study examines the association between class size, teacher characteristics and five non-cognitive student outcomes (i.e., self-control, interpersonal skills, approaches to learning, externalizing and internalizing problem behaviors) in grades K-3. Individual fixed-effects, that control for observed and unobserved time-invariant factors, including student and school time-constant variables, are employed to analyze national data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010–11 (ECLS-K:2011). Results suggest a significant linear association between reducing class size and interpersonal skills. Teacher experience is saliently, positively and significantly related with student self-control, interpersonal skills, and approaches to learning, and negatively associated with externalizing problem behaviors. Teacher education and certification were not associated with any of the five non-cognitive outcomes. Changing schools had a negative effect on student's self-control. [ABSTRACT FROM AUTHOR]

Relational density theory (RDT) attempts to model the nonlinearity of relational responding. Using concepts from classical mechanics, it predicts that volume—loosely defined as the number of members or nodes in a relational network—is inversely related to the density, or strength, of network relations and is directly related to the resistance to change of network relations. The present study tested two operational definitions of volume: class size and nodal distance. A match-to-sample protocol was used to establish four equivalence classes using a linear training structure. Density was measured as response accuracy or response latency during a mixed training and testing phase. Following this, one directly trained relation in each class was reconditioned and resistance to change was subsequently measured as change in response accuracy or latency following reconditioning. Results showed that nodal distance, but not class size, was inversely related to density and directly related to resistance. These findings have theoretical implications for the operational definition of volume in the context of predicting and influencing relational density and resistance and practical implications for the use of RDT concepts in applied domains. Limitations and suggestions for future research are discussed. [ABSTRACT FROM AUTHOR]

Hydrology education for hydrological professionals is an important field due to the complex and multifaceted water issues that hydrologists face. Currently, hydrology education at Chinese universities is mainly focused on hydrological engineering, which leads to inadequate scientific and professional training from the perspective of an interdisciplinary educational framework. In this context, the knowledge and skills of future hydrologists cannot be systematically prepared. In this study, we explore the challenges and constraints that hinder the advancement of hydrology education at Chinese universities by conducting an inductive analysis in which we compare the hydrology education that occurs in China with that of the United States. The result suggests that a lack of adequate financial support is the main constraint and that it leads to inevitable problems such as a high student-teacher ratio, insufficiently qualified educators, and poor teaching materials and equipment. To address this issue, financial support for this program should be increased. In addition, collaborative programs based on online learning can effectively resolve the inadequacy of teaching resources. Assessing the hydrological education system in American universities carries a certain significance for Chinese universities in creating a reasonable interdisciplinary hydrological educational system by emulating traditional engineering hydrological education. [ABSTRACT FROM AUTHOR]

Unplugged activities as a low-cost solution to foster computational thinking (CT) skills seem to be a trend in recent years. However, current evidence of the effectiveness of unplugged activities in promoting students' CT skills has been inconsistent. To understand the potential of unplugged activities on computational thinking skills, a systematic review and meta-analysis were conducted. Our review of 49 studies examined the influence of unplugged activities to improve students' CT skills in K–12 education between 2006 and 2022. The literature review showed that studies on CT skills were mainly (81.64%) conducted in computer science and STEM education, with board and card games being the most common unplugged activities for fostering CT skills in K–12 education. CT diagnostic tools (36.37%) were frequently used as assessment tools. A follow-up meta-analysis of 13 studies with 16 effect sizes showed a generally large overall effect size (Hedges's g = 1.028, 95% CI [0.641, 1.415], p < 0.001) for the use of unplugged activities in promoting students' CT skills. The analysis of several moderator variables (i.e., grade level, class size, intervention duration, and learning tools) and their possible effects on CT skills indicated that unplugged activities are a promising instructional strategy for enhancing students' CT skills. Taken together, the results highlight the affordances of unplugged pedagogy for promoting CT skills in K–12 education. Recommendations for policies, practice, and research are provided accordingly. [ABSTRACT FROM AUTHOR]

Many teachers strive for lively student participation in class. This field study examined aspects of learning environments in higher education with regard to their connection with students' oral engagement. Overall, six factors that might increase or decrease oral participation were investigated: the number of teacher questions, course atmosphere, level of demand, student preparation (e.g., through homework), class size, and subject discipline. The sample consisted of 80 courses of diverse disciplines at a public university in Germany; variables were measured by trained observers as well as by the attending students. Student oral participation was indicated by the number of student questions, the number of student contributions, and an engagement rate denoting the breadth of participation in a course. Three multiple regression analyses revealed a differentiated pattern of results: Whereas the number of student questions increased with the level of demand and a positive course atmosphere, the number of contributions and the breadth of participation were both closely linked to the number of teacher questions posed, but were also influenced by student preparation, level of demand, and the teaching culture of the subject discipline. Class size did not have a significant effect on any of the three participation measures. With respect to empirical research on student participation, the study shows the necessity for a differential approach and the consideration of teachers' interactive behaviour. Regarding the design of learning environments and the manner of teaching, three implications for practitioners are to ask questions, to be friendly, and to assign homework. [ABSTRACT FROM AUTHOR]

Hafting of stone tools and the creation of composite artifacts represent major developments in the early evolution of human technologies, with implications for artifact functions, human adaptation, and cognitive capabilities. A parallel issue is that of miniaturization of stone tools, which is argued to confer certain advantages, some of which are related to hafting. Our aim in this paper is to shift the discussion of these phenomena to the issues of re-hafting or retooling. We argue that important constraints on form and production of elements in composite implements come not just from the practice of hafting, but from the practice of rejuvenating implements by replacing broken or worn elements with similar-sized pieces. We further argue that absolute dimensional variation (tolerance) is the most important factor to consider in re-hafting or retooling. In this paper, we examine the hypothesis that there was a global increase in standardization in blade production over time related to increasing emphasis on hafting and retooling. Standardization is assessed in terms of both dimensional (sd), and relative (cv) measurements. The database for the study consists of > 100 assemblages, dating from the Middle Pleistocene to the Holocene. The data set includes a wide range of technologies ranging from comparatively simple to quite complex reduction. When the entire time range is examined, there is a decrease in blade size over time, and a parallel increase in standardization as measured by both sd and cv. However, the trend in cv is driven mainly by the late appearance of pressure blade technology; if pressure-blade technologies are excluded from the sample, there is no directional change in standardization as measured by cv. These findings suggest that prior to the widespread adoption of pressure blade technologies, Paleolithic knappers could create artifacts with finer dimensional tolerances only by making them smaller. The demands of increasing dependence on composite tools with replaceable parts could in turn explain long-term trends towards decreasing size in some classes of artifact. [ABSTRACT FROM AUTHOR]

Reproductive traits such as fecundity (i.e., the number of gametes produced) and the size and age of coral colonies at reproductive onset can vary in predictable ways among life history strategies. However, most studies on the onset of reproductive maturity in corals only report the presence or absence of oocytes with little known about variation in fecundity across size and age classes. This study aimed to determine the colony size and fecundity at the onset of reproductive maturity across size classes of two scleractinian corals with contrasting life history strategies, Acropora millepora (competitive) and Favites colemani (stress-tolerant). Colonies at a site in northwestern Philippines were sampled to determine the smallest colony size class with mature oocytes and to estimate fecundity across size classes. Histological slides were also prepared to verify the presence of mature gametes. Colonies were able to produce mature oocytes when they had attained colony diameters of 4.7 cm for A. millepora and 1.5 cm for F. colemani. A. millepora had lower fecundity, but larger oocytes compared to F. colemani. Although small colonies can contribute to the larval pool, the proportion of mature colonies increased for larger size classes, suggesting that larger colonies make a disproportionately greater contribution to population reproductive output. These findings contribute to our understanding of coral population dynamics, particularly in parameterizing population and demographic models for different coral life histories. [ABSTRACT FROM AUTHOR]

Semantic segmentation of remote sensing imagery (RSI) is critical in many domains due to the diverse landscapes and different sizes of geo-objects that RSI contains, making semantic segmentation challenging. In this paper, a convolutional network, named Adaptive Feature Fusion UNet (AFF-UNet), is proposed to optimize the semantic segmentation performance. The model has three key aspects: (1) dense skip connections architecture and an adaptive feature fusion module that adaptively weighs different levels of feature maps to achieve adaptive feature fusion, (2) a channel attention convolution block that obtains the relationship between different channels using a tailored configuration, and (3) a spatial attention module that obtains the relationship between different positions. AFF-UNet was evaluated on two public RSI datasets and was quantitatively and qualitatively compared with other models. Results from the Potsdam dataset showed that the proposed model achieved an increase of 1.09% over DeepLabv3 + in terms of the average F1 score and a 0.99% improvement in overall accuracy. The visual qualitative results also demonstrated a reduction in confusion of object classes, better performance in segmenting different sizes of object classes, and better object integrity. Therefore, the proposed AFF-UNet model optimizes the accuracy of RSI semantic segmentation. [ABSTRACT FROM AUTHOR]

This article begins with a historical overview of the STEM education policy and related classroom practices in Hong Kong. Against the backdrop that the Hong Kong education authority has been promoting STEM education over the past few years, there has been a pressing need for effective strategies of implementing STEM education in the context of reduced class size classrooms (i.e. small class teaching). With a view to addressing this need, this article strives to exemplify the incorporation of STEM education into small class teaching settings. Intended as a conceptual paper drawing on design approaches for STEM lessons and a small class teaching framework, the article demonstrates the relevance of STEM education to small class teaching. Two illustrative lesson design examples are provided to showcase how the design approaches and framework can be operationalised. In addition, the article also offers a thoughtful discussion concerning the potential challenges of delivering the two sample lessons as well as the coping strategies. It contributes to understanding of STEM education theories and provides a valuable reference for educational practitioners. [ABSTRACT FROM AUTHOR]

Research identifying the core features of Growth Mindset Pedagogy (GMP) in Chinese mathematics education is limited. This is also the first time we have examined the barriers to implementing GMP. We used semi-structured interviews to collect data. By analyzing the interview data, we identified four core features of GMP in mathematics classrooms: differentiation as the foundation of pedagogical practice, no stereotypes about mathematics learning, encouraging students to think in a process-oriented manner, and promoting a persistent learning attitude. We also found five barriers to GMP implementation: (a) lack of professional support; (b) lack of time; (c) student differences and class size; (d) ignoring cultural contextual elements; and (e) poor partnership between parents and teachers. In our discussion section, we outlined the implications of these findings for research and practice in educational contexts. [ABSTRACT FROM AUTHOR]

Institutions of higher education often have multiple entry points for first-time and transfer college students to engage in high-impact educational practices (HIPs), well documented to advance student learning outcomes. Some students may seek out repeated opportunities while others engage very little or not at all in activities such as student-faculty research, study abroad, internships, first-year cohort programs, service-learning, and the like. When institutions maintain decentralized data and records on students' participation, obtaining a true understanding of the "who, what, when, and where" of HIPs can be difficult. In this paper, we present an institutional strategy for longitudinal collection of data for nearly 5,000 entering students across six years and nine different categories of HIPs, and we discuss the opportunities and implications of performing such a study. Additionally, we provide examples of how disaggregation of student data is crucial for using the results to improve curriculum and resource alignment for institutional research and institutional change purposes, supporting the goal of inclusive and equitable college engagement portfolios for all students. [ABSTRACT FROM AUTHOR]

In higher education, low teacher-student ratios can make it difficult for students to receive immediate and interactive help. Chatbots, increasingly used in various scenarios such as customer service, work productivity, and healthcare, might be one way of helping instructors better meet student needs. However, few empirical studies in the field of Information Systems (IS) have investigated pedagogical chatbot efficacy in higher education and fewer still discuss their potential challenges and drawbacks. In this research we address this gap in the IS literature by exploring the opportunities, challenges, efficacy, and ethical concerns of using chatbots as pedagogical tools in business education. In this two study project, we conducted a chatbot-guided interview with 215 undergraduate students to understand student attitudes regarding the potential benefits and challenges of using chatbots as intelligent student assistants. Our findings revealed the potential for chatbots to help students learn basic content in a responsive, interactive, and confidential way. Findings also provided insights into student learning needs which we then used to design and develop a new, experimental chatbot assistant to teach basic AI concepts to 195 students. Results of this second study suggest chatbots can be engaging and responsive conversational learning tools for teaching basic concepts and for providing educational resources. Herein, we provide the results of both studies and discuss possible promising opportunities and ethical implications of using chatbots to support inclusive learning. [ABSTRACT FROM AUTHOR]

Based on public data such as the Educational Statistics Yearbook and the National Statistics Yearbook, this paper analyzes the equalization trend of fundamental education in the Tibet Autonomous Region (hereinafter referred to as Tibet), China, using data on running conditions in primary and middle schools in Tibet from 2013 to 2020, and carries out clustering of the rankings of data from China in 2020. The results show that the equalization level of primary and middle education in Tibet has continuously improved from 2013 to 2020. This is evidenced by the increases and improvements in education funding per student, student-teacher ratios, numbers and academic qualifications of teachers, per capita teaching areas and per capita teaching assets. In 2020, the per student education fee in Tibet took the lead in China's 31 provincial regions, and the student-teacher ratio was close to the national average. Running conditions in primary and middle schools in Tibet still require improvement. This is reflected in the low proportion of full-time teaching staff in primary and middle schools, lack of teachers with senior professional titles in middle schools, area of auxiliary teaching facilities (laboratories, computer rooms, gymnasiums, etc.) in middle schools, and especially in high schools, and shortage of teaching assets (books, computers, multimedia classrooms) in middle schools. [ABSTRACT FROM AUTHOR]

Teachers' spatial behaviours in the classroom can strongly influence students' engagement, motivation and other behaviours that shape their learning. However, classroom teaching behaviour is ephemeral, and has largely remained opaque to computational analysis. Inspired by the notion of Spatial Pedagogy, this paper presents a system called 'Moodoo' that automatically tracks and models how teachers make use of the classroom space by analysing indoor positioning traces. We illustrate the potential of the system through an authentic study with seven teachers enacting three distinct learning designs with more than 200 undergraduate students in the context of science education. The system automatically extracts spatial metrics (e.g. teacher-student ratios, frequency of visits to students' personal spaces, presence in classroom spaces of interest, index of dispersion and entropy), mapping from the teachers' low-level positioning data to higher-order spatial constructs. We illustrate how these spatial metrics can be used to generate a deeper understanding of how the pedagogical commitments embedded in the learning design, and personal teaching strategies, are reflected in the ways teachers use the learning space to provide support to students. [ABSTRACT FROM AUTHOR]

Electronic assessment (e-assessment) is an essential part of higher education, not only used to manage a large class size of students' learning performance and particularly in assessing the learning outcomes of students. The e-assessment data generated can not only be used to determine students' study weaknesses to develop strategies for teaching and learning, but also in the development of essential teaching and learning pedagogies for online teaching and learning. Despite the wider adoption of Information and Communication Technology (ICT) technologies due to the COVID-19 pandemic, universities still encountered numerous problems during the transformation to electronic teaching as most educators struggled with the effective implementation of the Electronic Assessment System (EAS). The successful launch of EAS relied heavily on students' use intention towards the new and unfamiliar electronic system, which was actually unknown to the project managers of EAS. It is therefore important to understand students' views and concerns on EAS and the proactive measures taken by universities to enhance students' acceptance and intention of usage. Although most studies investigate students' acceptance of online learning, there is still little research on the adoption of e-assessment. In this regard, we propose to develop a theoretical model based on students' perceptions of EAS. Based on the Technology Acceptance Model (TAM) and a major successor of TAM, an electronic assessment system acceptance model (EASA model) is developed with key measures including system adoption anxiety, e-assessment facilitation, risk reduction amid, etc. The data is obtained through a survey among current students at a local university, and structural equation modeling (SEM) is applied to analyze the quantitative data. This study has a significant impact on improving educators' use of e-assessment in order to develop essential online teaching and learning pedagogy in the future. [ABSTRACT FROM AUTHOR]

Early childhood educators (birth through second grade) have faced a wide range of challenges while providing education and care for the youngest group of children. Their positions often range from child-care settings to grade school, with different configurations for benefits, class size, and salary. During the first year of the COVID-19 pandemic, 192 early educators shared their perceived stress levels and personal and employment context including relationship status, caregiving responsibilities, education level, work setting, and age group. While there were noted differences across the group, educators working in school-aged settings and those who were caregivers (outside of work) reported higher levels of stress. Interview results from a subset of survey respondents showed concerns about online learning and the well-being of their students, while also underscoring personal growth through the challenges. [ABSTRACT FROM AUTHOR]

Let be a group. Define an equivalence relation on as follows: for , if and have same order. The set of sizes of equivalence classes with respect to this relation is called the same-order type of . Let and denote the number of elements of order and the set of element orders of the finite group , respectively. Shen (2012) posed the following conjecture: let be a group of order with same-order type , and let . If and for , then . If , then there is no such group. In this paper, we give a partial answer to this conjecture. In fact, for with a counterexample, we give negative answer to the above conjecture, and for , we find that above conjecture holds for finite -groups of nilpotency class less than . [ABSTRACT FROM AUTHOR]

Morphological changes in a river are mainly governed by effective discharge which is known to be sensitive to class size/number. The present paper compares the effective discharge computed by commonly used approaches for deciding class size/number, viz., standard iterative approach, pre-determined class size/number, and logarithmic class interval. The discharge and sediment data of fifteen gauging sites along the Ganga river have been utilized to study the effect of class size on the effective discharge. Over the years, different approaches have been used to decide the number of classes in effective discharge computation; therefore, it was necessary to compare different approaches so that rational procedure may be adopted to compute effective discharge. Results of the present study indicate that the computation of effective discharge based on pre-determined number/size of class may lead to erratic load histogram with many classes of discharge transporting zero sediment load. Logarithmic class intervals may lead to the overestimation of effective discharge. The application of standard iterative approach for deciding class size for effective discharge computation appears to be most appropriate. Further, an equation has been proposed to estimate the ratio of bankfull discharge to effective discharge at ungauged sites of the Ganga River. The ratio of bankfull discharge to effective discharge was found to be 2.12 on an average signifying deep incision. However, the ratio of bankfull discharge to effective discharge was found to be 1.14 and 1.13 at Gandhighat and Hathidah, respectively. [ABSTRACT FROM AUTHOR]

Community colleges have been under pressure for years to improve retention rates. Considering well-publicized reductions in state funding during and after the Great Recession, progress in this area is unexpected. And yet this is precisely what we find. Using the Integrated Postsecondary Education Data System (IPEDS), we find an average increase in retention of nearly 5 percentage points, or 9 percent, across the sector from 2004 to 2017. Over 70% of institutions posted retention gains, and average improvement occurred yearly over the period excepting a reversal at the height of the Great Recession. Gains were smaller on average at schools with higher tuition and that serve more disadvantaged populations, and larger at institutions with lower student-faculty ratios and higher per-student instructional spending. Fixed-effects regression and Oaxaca decomposition analyses demonstrate that these gains were not caused by observable changes in student body composition or in institutional characteristics such as increased per-student instructional spending. [ABSTRACT FROM AUTHOR]

Migrants' socio-economic integration is a major theme in migration research, which can provide economic and cultural benefits. And it will contribute to social stability. The investigation from the spatial perspective should also be considered. This paper aims to examine the spatial differentiation of the socio-economic integration of migrants and identify its driving forces to provide crucial evidence and policy recommendations to urban policymakers and further improve migrants' socio-economic integration. Based on the latest China Migrants Dynamic Survey, this paper uses global Moran's I index, hot spot analysis and GWR model to explore spatial differentiation and driving forces of the socio-economic integration of 155,789 migrants in 291 cities at prefecture level and above in China. The results show that: (1) The socio-economic integration of migrants consists of five dimensions, which are economic integration, cultural integration, social security, social relation and psychological integration. Among them, psychological integration is the highest (73.16) and economic integration is the lowest (13.38). (2) The socio-economic integration of migrants is mainly influenced by their own characteristics instead of the destination characteristics. Four factors (age, education, length of stay and population growth rate) positively affect migrants' socio-economic integration, while three factors (inter-provincial mobility, proportion of tertiary industry in GDP, and ratio of teacher to student in middle school) negatively impact the socio-economic integration of migrants. (3) The socio-economic integration of migrants shows the distribution pattern of agglomeration. And the integration also presents a significant spatial heterogeneity. The driving forces of the socio-economic integration exhibit various zonal spatial differentiation patterns, including "E–W", "SE–NW", "NE–SW", and "S–N". Finally, some useful recommendations are given for improving migrants' socio-economic integration. [ABSTRACT FROM AUTHOR]

We aim to identify those measures that effectively control the spread of SARS-CoV-2 in Austrian schools. Using cluster tracing data we calibrate an agent-based epidemiological model and consider situations where the B1.617.2 (delta) virus strain is dominant and parts of the population are vaccinated to quantify the impact of non-pharmaceutical interventions (NPIs) such as room ventilation, reduction of class size, wearing of masks during lessons, vaccinations, and school entry testing by SARS-CoV2-antigen tests. In the data we find that 40% of all clusters involved no more than two cases, and 3% of the clusters only had more than 20 cases. The model shows that combinations of NPIs together with vaccinations are necessary to allow for a controlled opening of schools under sustained community transmission of the SARS-CoV-2 delta variant. For plausible vaccination rates, primary (secondary) schools require a combination of at least two (three) of the above NPIs. How to safely maintain open schools during a pandemic is still controversial. Here, the authors aim to identify those measures that effectively control the spread of SARS-CoV-2 in Austrian schools, with an agent-based mathematical model. [ABSTRACT FROM AUTHOR]

Unlike design studio, preparatory modules in the undergraduate Architecture course typically have a high student–teacher ratio and are conducted in a traditional lecture setting. By nature, lecture setting hinders engagement and reduces motivation, eventually lowering student learning outcomes. This study aimed to increase engagement with the content, lecturer, and among peers in a traditional lecture and consequently improve higher cognitive learning outcomes. Wi-Fi-enabled devices as clickers were used in all lectures to implement "pause and recall" with ConcepTests to increase participation and interaction. Lectures were paused every 15–20 min, and students were asked questions of higher cognitive order that required them to apply the concepts covered in an online platform that acted as clickers. For this quasi-non-experimental mixed-method study, 79 students' approach to learning before and after the intervention, perception of using clickers, and learning outcomes were measured for a preparatory module, Environmental Systems in the undergraduate Architecture program. Learning outcomes were measured at various cognitive levels based on Bloom's taxonomy. Students' deep approach to learning increased at the end of the semester (Cohan's d = 0.277 and 0.216 for deep motive and strategy, respectively). Students generally have a positive perception and those who showed a positive attitude towards using clickers achieved better scores at higher cognitive questions in the final test (rs = 0.359, p = 0.001). Students with a deep strategy approach to learning reflected increased self-evaluation (rs = 0.275, p = 0.022) and study behavior (rs = 0.263, p = 0.029) to use clickers. Clickers used to pose 'ConcepTest' questions to execute "pause and recall" in a large lecture class had a positive impact on student performance. Semi-structural interviews were performed to further explain the findings. Results were consistent with the generative theory of learning. The timing and design of clicker questions followed by a discussion were particularly beneficial in improving critical thinking among students. [ABSTRACT FROM AUTHOR]

In the past 20 years, defect prediction studies have generally acknowledged the effect of class size on software prediction performance. To quantify the relationship between object-oriented (OO) metrics and defects, modelling has to take into account the direct, and potentially indirect, effects of class size on defects. However, some studies have shown that size cannot be simply controlled or ignored, when building prediction models. As such, there remains a question whether, and when, to control for class size. This study provides a new in-depth examination of the impact of class size on the relationship between OO metrics and software defects or defect-proneness. We assess the impact of class size on the number of defects and defect-proneness in software systems by employing a regression-based mediation (with bootstrapping) and moderation analysis to investigate the direct and indirect effect of class size in count and binary defect prediction. Our results show that the size effect is not always significant for all metrics. Of the seven OO metrics we investigated, size consistently has significant mediation impact only on the relationship between Coupling Between Objects (CBO) and defects/defect-proneness, and a potential moderation impact on the relationship between Fan-out and defects/defect-proneness. Other metrics show mixed results, in that they are significant for some systems but not for others. Based on our results we make three recommendations. One, we encourage researchers and practitioners to examine the impact of class size for the specific data they have in hand and through the use of the proposed statistical mediation/moderation procedures. Two, we encourage empirical studies to investigate the indirect effect of possible additional variables in their models when relevant. Three, the statistical procedures adopted in this study could be used in other empirical software engineering research to investigate the influence of potential mediators/moderators. [ABSTRACT FROM AUTHOR]

This article analyzes cross-national trends in national student-faculty ratios (SFRs) over the past five decades. In descriptive analyses, we find that SFRs have increased globally, driven by particularly large increases in low-income countries. We analyze two cross-national datasets to examine factors associated with national SFRs. We find that national SFRs are positively associated with gross tertiary enrollment rates and particularly so in low-income countries. In contrast, both the female share of faculty and research spending are associated with having lower national SFRs. The findings shed light on how national higher education systems are responding to massification pressures and suggest that differentiating faculty roles is one way that countries curb their rising SFRs as enrollments grow. [ABSTRACT FROM AUTHOR]

There is a pressing need for evidence-based scrutiny of plans to re-open childcare centres during the COVID-19 pandemic. Here we developed an agent-based model of SARS-CoV-2 transmission within a childcare centre and households. Scenarios varied the student-to-educator ratio (15:2, 8:2, 7:3), family clustering (siblings together versus random assignment) and time spent in class. We also evaluated a primary school setting (with student-educator ratios 30:1, 15:1 and 8:1), including cohorts that alternate weekly. In the childcare centre setting, grouping siblings significantly reduced outbreak size and student-days lost. We identify an intensification cascade specific to classroom outbreaks of respiratory viruses with presymptomatic infection. In both childcare and primary school settings, each doubling of class size from 8 to 15 to 30 more than doubled the outbreak size and student-days lost (increases by factors of 2–5, depending on the scenario. Proposals for childcare and primary school reopening could be enhanced for safety by switching to smaller class sizes and grouping siblings. [ABSTRACT FROM AUTHOR]

In the traditional brick-and-mortar classroom, small classes are generally perceived as desirable, but the benefits associated with particular class sizes in online education have not yet received much scholarly attention. Using a dataset of 10,648 enrollment records generated during the 2013-2014 school year at a state virtual school in the Midwestern U.S., this study examined the relationship between class size and student learning outcomes. The results of hierarchical linear modeling with fractional polynomial analysis suggest a reverse-U-shaped relationship, in which increasing online class sizes had a positive impact on achievement until the number of students reached 45, but a negative one if numbers increased beyond that level. At the subject level, similar reverse-U-shaped patterns were observed in math, social science, and other subjects, but not in English, foreign languages, or science. [ABSTRACT FROM AUTHOR]

Here or There (HOT) instruction is a blended synchronous approach that enables students from on-campus ("here") or a remote location ("there") to participate together in class activities in real time. The purpose of this article is to share three different cases at two universities that illustrate different implementations of HOT instruction, explain the affordances of these varied approaches, provide best practices that are common to each, and share lessons learned along the way. Readers will gain a better understanding of how to implement a range of innovative HOT approaches, and in what context(s) they might choose one approach over another. The authors' experience indicates that sound pedagogical principles along with pragmatic considerations, such as class size, available technology, and instructor's skills, should guide decisions regarding use of these blended synchronous approaches. Future research should look towards what impact blended synchronous environments have on student outcomes. [ABSTRACT FROM AUTHOR]

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Seeing the relevance of tasks for future use is important for developing value and interest in them. We employed a pre- and post-test quasi-experimental design using a mixed-methods approach to examine if reflecting on the relevance of technology to future teaching practices influences elementary and secondary preservice teachers’ utility value and interest toward technology integration. The findings from 111 preservice teachers revealed that reflecting on the connections of technology to future teaching increased their maintained interest in technology integration regardless of their situational interest levels. Reflections also helped them recognize technology-supported classroom management strategies in their current implementations. Differences observed between elementary and secondary preservice teachers highlighted a need for helping secondary preservice teachers develop higher interest and deeper understanding of utility values of technologies for future practices. Results also underscored the importance of emphasizing various benefits of technology regarding collaboration, assessment, and self-paced learning—utility values that were minimally observed in the study. [ABSTRACT FROM AUTHOR]

With increasing class sizes, teachers and facilitators alike hope for learning groups where students work together in self-contained and autonomous ways requiring reduced teacher support. Yet many instructors find the idea of developing independent learning in small groups to be elusive particularly in K-12 settings (Ertmer and Simons in Interdiscip J Probl Based Learn 1(1):5, doi:10.7771/1541-5015.1005, 2006; Simons and Klein in Inst Sci 35(1):41-72, 2007). Autonomy in small learning groups is actively promoted in many of the forms of problem-based learning (PBL). A PBL learning group is traditionally defined as students with tutor assigned to the group. However, as PBL is introduced into K-12 environments, the assumption of group autonomous functioning is tenuous for a variety of reasons. The purpose of this research is to determine the extent to which a K-12 PBL learning group functions in autonomous ways when a computer-based scaffold provides some student support normally provided by the teacher or tutor during a PBL environmental science unit. If a computer-based scaffold can successfully enable key elements of autonomous group functioning by supplying process level support normally provided by a tutor or teacher, K-12 teachers anxious to attempt PBL may be able to venture with greater confidence that they can provide multiple learning groups adequate support. Results suggest that a computer-based scaffold informed by Moore’s transactional distance theory can promote process elements of autonomous group functioning. [ABSTRACT FROM AUTHOR]

Stampede accidents have become the major threat to campus security in China. In order to grasp the occurrence regularity of campus stampede accidents in China and to prevent the accidents, statistical analysis methods and case analysis methods were employed to study the temporal and spatial characteristics and inducing factors of campus stampede accidents in China during 2000-2014. The results showed that the occurrence frequency and casualties of campus stampede accidents in China had larger inter-annual changes and presented a decreasing trend overall. Autumn had the largest occurrence frequency and casualties, respectively, accounting for 63 and 74%; winter took the second; and spring and summer were the least. Campus stampede accidents in China were distinct in week variation and an existed Monday phenomenon. Monday had the largest occurrence frequency and casualties, respectively, accounting for 32.4 and 23.1%. Campus stampede accidents in China mostly occurred in south-central China, and in the northwest and southwest borderlands. 92.3% of stampede accidents occurred on stairs. Primary schools had the highest occurrence frequency and casualties, occupying 71.2 and 60.7%. Education fund input, student-teacher ratio, and students' enrollment had significant impact on campus stampede accidents in China. [ABSTRACT FROM AUTHOR]

As growing numbers of social work programs offer online delivery of course content, the positive aspects described in the literature, such as student access and flexibility, as well as concerns about quality, instructor/student relationships, and academic honesty of students, need to be examined as they relate to clinical social work education (Pelech et al. ; Reamer ). Three examples of fully online courses offered to clinical social work students by an experienced clinician and online instructor are examined in the context of the benefits and challenges put forth in the literature. A foundation interviewing course, diagnostic assessment course, and course on social work with older adults with a service-learning component are described in terms of quality, comparison to face-to-face courses, advantages, and disadvantages. These examples illustrate that online courses which are strategically and rigorously developed are comparable to face-to-face courses in many ways, including activities, assignments, assessments, outcomes, student quality, and methods of addressing academic dishonesty. Yet, differences exist in quality and quantity of interaction and skill development. Methods of ensuring quality are explored, including intense instructor presence, real time meetings online, and well-formulated discussion questions that require students to interact with the material and each other in ways that are potentially more demanding and engaging than courses taught face-to-face. Further challenges of technology, class size and requirement of additional faculty time are discussed, as well as clinical content that is currently more appropriately taught with a face-to-face component. [ABSTRACT FROM AUTHOR]

Prior research suggests that the benefits from smaller classes may vary along multiple dimensions. In this paper we develop a flexible model of education production that incorporates the classroom-level time lost to disruption and the rate of learning during productive time as a function of teacher quality and individual propensity to acquire knowledge. We then investigate heterogeneity in class size effects by school poverty share, family income, teacher experience, and achievement percentile using data from Project STAR. We find that the benefits of small classes are consistently higher in schools with a larger low-income enrollment share. Conditional on school poverty share, we find little or no evidence that lower-income or lower-achieving students tend to realize larger benefits of smaller classes. Instead, we find that the return to smaller classes tends to increase with achievement regardless of school poverty share. Given the generally higher levels of disruption reported in higher poverty schools, this set of findings is consistent with, though not direct evidence of, the notion that reduced time lost to disruption is a primary mechanism through which smaller classes raise achievement and a compelling explanation for the empirical finding that class-size effects tend to be larger for lower-income children. [ABSTRACT FROM AUTHOR]

With an increasing percentage of schools moving toward approaches to data-based instructional problem-solving and early remediation of learning difficulties, the development and execution of intervention plans often warrants the pragmatic question: How intensive should an intervention be so that it is effective, while also feasible and time efficient to implement? In other words, educators must prudently balance treatment intensity, anticipated effectiveness, and available implementation resources. This study examined the effects of an evidence-based reading fluency intervention that included the same instructional components but was implemented with varying treatment durations and student-teacher ratios. Using an alternating-treatments design, four second-grade struggling readers received four treatment conditions (small group with ~14 min of intervention; small group with ~7 min of intervention; one on one with ~14 min of intervention; and one on one with ~7 min of intervention) and a no-intervention control condition. Using three data-analytic strategies and two dependent measures, overall findings suggested that all intervention conditions led to reading improvements but that (a) the longer intervention duration appeared more effective than the shorter duration, and (b) there was little difference in intervention effectiveness between the small-group and one-on-one conditions. [ABSTRACT FROM AUTHOR]

Both lecture delivery and Facebook use are ubiquitous aspects of higher education from staff and student points-of-view, respectively. An attempt was made to integrate the two by setting up a Facebook group and delivering contemporary news stories in preparation for in-lecture discussion in a large-scale (1,200 students across 5 sections) Introduction to Psychology class. Each section experienced two-thirds of the class with Facebook intervention and one-third without, thereby each section served as its own control group. Overall, Facebook intervention did not yield higher self-report of course engagement or understanding for those portions of the course. Only those individuals who never viewed the Facebook postings reported lower engagement and understanding of the in-lecture discussion, in addition to a lower appreciation of the link between the Facebook content and the lecture material. Our data suggest that successful integration of social media into the classroom is a challenging one and the relative success or failure of these interventions may stand or fall on the basis of a complex interaction between a number of factors including the timing of content delivery, the integration of social media content with course assessment and the students' own perspective on using social media for academic purposes. [ABSTRACT FROM AUTHOR]

Class reuse-proneness is the likelihood that a class can be reused and is a key quality characteristic in object-oriented design. Because it is clearly impossible to know with certainty when, where, how, and how often a class will be reused, this likelihood can only be estimated when a class is developed. At that stage, the internal quality attributes of a class such as cohesion, coupling, and size can be measured. In this paper, we empirically study the ability of 29 internal class quality measures, individually and in combination, to estimate class reuse-proneness. Specifically, we take into account both class inheritance and class instantiation, which are two ways in which a class can be reused. Our results show that most of the considered measures are predictors for the considered reuse-proneness attributes to some degree. The capability of the considered internal quality measures to predict class reuse-proneness is enhanced when the measures are combined using an optimized multivariate statistical model. The results also show that the size and coupling attributes of a class have positive impacts on its reuse-proneness via inheritance and instantiation. The cohesion of a class has a negative impact on its inheritance reuse-proneness and a positive impact on its instantiation reuse-proneness. The overall results of the empirical study show that software developers can use a number of predictors to assess the reuse-proneness of classes and possibly improve the reuse-proneness of the classes by controlling their internal quality attributes. Our results contribute to the evaluation of the quality of a class, but a comprehensive evaluation of the quality of a class should take into account many more qualities. Also, not all classes in a software system are built with reuse-proneness in mind, so our results should be applied only to those that are designed and implemented to be reusable. [ABSTRACT FROM AUTHOR]

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As in many universities, class sizes have increased more quickly than teaching and learning resources. A related challenge is the increasing diversity of the student body in terms of socio-economic background, learning styles, English language ability and preparedness. This paper explores ways in which traditional face-to-face teaching methods (such as lectures and tutorials) can be combined with online teaching and learning activities in a 'blended' learning approach to improve teaching and learning and to accommodate student diversity. Using a large first year Economics class as a case study, data were collected on student perceptions of the use of blended learning. A statistical model was used on a sample of 50 students to determine which online activities were most beneficial in improving student performance. The majority of students agreed that replacing one lecture a week with online activities and resources improved their learning, although about 20 % of the class would have preferred more lecturing and fewer online resources. Statistical finding showed that more active online resources, such as multiple choice and graphing questions, were most beneficial in improving student performance, but that more passive lecture capture was also useful in modelling the discourse of the discipline. [ABSTRACT FROM AUTHOR]

In South Africa and in other parts of the world, many professions are bemoaning the poor ability of many graduates to communicate their skills and knowledge effectively once they enter the workplace. Increasingly, pressure is placed on higher education to do more in terms of equipping future professionals with the necessary critical reading, research, thinking and writing skills the workplace demands. However, in South Africa especially, the demand for access to higher education is resulting in increased admissions, and in many lecturers standing in front of larger classes filled with students from a wide range of home and educational backgrounds with 'variable' commands of English as a medium of instruction and communication (Greenbaum and Mbali in S Afr Linguist Appl Lang Stud 20:233-244, ). This makes the task of equipping these students with disciplinary knowledge and skills a challenge. In responding to this challenge, the Law Faculty at the University of the Western Cape, in collaboration with a writing specialist, initiated a project aimed at transforming the way in which legal writing was taught at first year level. The overall aim was to start training students, from first year, to adapt their thinking and writing to the kinds of knowledge and practice required by academic study as well as the legal profession. The project was successful in achieving its modest aims, but certain challenges remain. This paper reflects critically on the development and evolution of the model for teaching legal writing in large classes. It argues that teaching legal writing in large classes requires creative and sustainable approaches so that students can become active and critical writers, readers and thinkers over time in this, or any, field. [ABSTRACT FROM AUTHOR]

In this article I examine the role of the contemporary university in light of the mass increase in class sizes that has occurred on an international scale. While we may look nostalgically back to a time when lectures numbered a few hundred students and tutorials had as few as ten, massification at undergraduate level is an inescapable fact of academic life today. I argue that this development is an opportunity and a challenge for lecturers and particularly teacher-researchers, who can and have risen to this challenge to strive for better and more creative teaching practices, without compromising the quality of content or delivery. I outline some of the strategies that I have employed with my first year sociology cohort, which numbers over 1,000 students, and the satisfaction and inspiration that comes from successfully reaching out to such a large student population. In addition, I canvas the positive impacts that derive from including students in the course development process, including to the extent that their input contributes to pedagogical research. [ABSTRACT FROM AUTHOR]