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Rob Cavanagh - One of the best experts on this subject based on the ideXlab platform.

  • A unified model of student engagement in Classroom Learning and Classroom Learning environment: one measure and one underlying construct
    Learning Environments Research, 2015
    Co-Authors: Rob Cavanagh
    Abstract:

    This study employed the capabilities-expectations model of engagement in Classroom Learning based on bio-ecological frameworks of intellectual development and flow theory. According to the capabilities-expectations model, engagement requires a balance between the capabilities of a student for Learning in a particular situation and what is expected of that student’s Learning. The study also used an eight-element model of the Classroom Learning environment (self educational values, self Learning outcomes, Classroom/peer Learning attitudes and behaviours, Classroom/peer support, Classroom/peer discussion, Classroom planning, teacher support and expectations, and parental involvement). The aim was to test the assumption that engagement in Classroom Learning and perceptions of the Classroom Learning environment both indicate the same uni-dimensional construct. If this assumption is correct, then it should be possible to plot measures of student engagement and measures of the Learning environment on the same linear scale. A measurement model such as the Rasch Model can then be used to test how well empirical data fit the scale. An 85-item rating scale survey of student engagement in Classroom Learning and the Classroom Learning environment scale was created. Data from its administration to 1760 secondary school students were tested for fit to the Rasch Rating Scale Model. Data on engagement in Classroom Learning and the Classroom Learning environment were able to be plotted on one interval scale, therefore suggesting the presence of the underlying common construct. The construct was called an engaging Learning environment.

  • Associations between the Classroom Learning Environment and Student Engagement in Learning 1: A Rasch Model Approach.
    2012
    Co-Authors: Rob Cavanagh
    Abstract:

    This report is about one of two phases in an investigation into associations between student engagement in Classroom Learning and the Classroom Learning environment. Both phases applied the same instrumentation to the same sample. The difference between the phases was in the measurement approach applied. This report is about application of the Rasch model to analyse the data; the second report (Associations between the Classroom Learning Environment and Student Engagement in Learning 2: A Structural Equation Modeling Approach), is about Structural Equation Modeling application. Student engagement in Learning has become an important consideration in research into Learning environments and the design of instruction. This study applied a novel model of engagement in Classroom Learning based on flow theory and bio-ecological frameworks. The objectives were to construct a composite measure of student engagement in Classroom Learning and the Classroom Learning environment. Then, to compare student scores for variables and groups of students (e.g. boys and girls). An 85-item scale was created and data from administering the scale to 1760 secondary school students were tested for fit to the Rasch rating scale measurement model. Data on engagement in Classroom Learning and the Classroom Learning environment were able to be plotted on one interval scale suggesting an underlying common construct. Also, there were statistically significant differences in overall student scores between country and city students, boys and girls, year cohorts, curriculum areas, and favourite and non-favourite subjects.

  • Associations between the Classroom Learning Environment and Student Engagement in Learning 2: A Structural Equation Modelling Approach
    2012
    Co-Authors: Allen G. Harbaugh, Rob Cavanagh
    Abstract:

    This report is about the second of two phases in an investigation into associations between student engagement in Classroom Learning and the Classroom-Learning environment. Whereas the first phase utilized Rasch modelling (Cavanagh, 2012), this report uses latent variable modelling to explore the data. The investigations in both phases of this study employed a novel model of engagement in Classroom Learning based on flow theory and bio-ecological frameworks. An 85-item survey item was used to collect data from 1760 secondary-school students. Comparable to the findings of the first phase, there was strong evidence for the psychometric properties of the instrument measuring the latent constructs of student engagement in Classroom Learning and the characteristics of the ClassroomLearning environment. Furthermore, Classroom-Learning environment characteristics had direct effects on students’ self-esteem and had direct and indirect effects on students’ expectations of the Classroom environment. Classroom characteristics directly influencing students’ self-esteem included the educational values, Learning outcomes, Classroom Learning and parental support. Classroom characteristics directly influencing students’ expectations included the educational values, Learning outcomes, Classroom Learning, support from fellow students and expectations of the teacher. Among other benefits, the two phases of this study enable comparison of contemporary analytic approaches: Rasch and Structural Equation Modelling.

  • Associations between the Classroom Learning environment and student engagement in Learning 2: A structural equation modeling approach
    2012
    Co-Authors: Allen G. Harbaugh, Rob Cavanagh
    Abstract:

    Purpose This report is about the second of two phases in an investigation into associations between student engagement in Classroom Learning and the Classroom-Learning environment. The same instrument was used in both phases, and the sample of the current study was a subset of the larger sample used in the first phase. The difference between the phases was in the measurement approach applied. This report is about the application of latent variable modeling to explore the data; the previous report (Associations between the Classroom Learning Environment and Student Engagement in Learning 1: A Rasch Model Approach) utilized Rasch Modeling to analyze the data Student engagement in Learning is an important consideration for research into Learning environments and instructional design. The investigations in both phases of this study employed a novel model of engagement in Classroom Learning based on flow theory and bio-ecological frameworks. The objectives of the phase reported here were (1) to assess the psychometric properties of the instrument measuring the latent constructs of student engagement in Classroom Learning and the characteristics of the Classroom-Learning environment, and (2) to use structural equation modeling (SEM) to explore potential relationships between student engagement and Classroom environment. The hypothesis of the SEM approach was that specific Classroom-Learning environment elements would be predictive of student engagement in Learning. Method Using the 85-item rating scale instrument created for the first phase of this study, 26 of 27 items were retained as a measure student engagement, and 35 of 58 items were retained to measure 7 characteristics of the Classroom-Learning environment. The self-report instrument was administered to 1760 secondary school students in metropolitan country regions of Western Australia. The computer program R was used for data analysis. After confirming the psychometric properties of the measurement model, factor scores were extracted and used in the SEM analysis. Results Classroom-Learning environment characteristics had direct effects on students' self-esteem and had direct and indirect effects on students' expectations of the Classroom environment. Classroom characteristics directly influencing students' self-esteem included the educational values, Learning outcomes, Classroom Learning and parental support. Classroom characteristics directly influencing students' expectations included the educational values, Learning outcomes, Classroom Learning, support from fellow students and expectations of the teacher. Conclusion The investigation is an important contribution to knowledge and theorizing about student engagement and Classroom Learning environments. The two reports enable comparison of contemporary analytic approaches ? Rasch and Structural Equation Modeling.

  • The engagement in Classroom Learning of Years 10 and 11 Western Australian students
    Applications of Rasch Measurement in Learning Environments Research, 2011
    Co-Authors: Penelope Kennish, Rob Cavanagh
    Abstract:

    The consideration of issues related to student engagement in Classroom Learning has taken on increasing importance in Western Australia since the passing of legislation to raise the school leaving age to 17 years, which came into effect in 2008. There are now more students retained at schools in Years 11 and 12 than previously. Engaging these students in Learning is of the upmost importance for secondary schools. This paper presents a hypothesised model of student engagement in Classroom Learning that is based on the principles of Flow Theory (i.e. a person achieves a state of flow when there is a match in high skills and high challenges). The hypothesised model proposes that student engagement occurs when there is a balance between student Learning capabilities (skills) and the expectations of student Learning (challenges). Each of these comprised sub-constructs, of which there were 11 in total. The research sought to determine which of the 11 subconstructs that comprise the student engagement in Classroom Learning were the most difficult and which were easier to identify in Year 10 and 11 students. It also sought to determine whether membership of different groups of students accounted for variance in the calibrated scores (these groups being gender; school year; subject; and whether it was a favourite or least favourite subject). The sample comprised 112 Year 10 and 11 students from metropolitan and rural government schools in Western Australia. Each student was assigned a rating from zero to five by two researchers on each of the 11 sub-constructs. The Rasch Rating Scale Model was used for analysis of the quantitative data. Firstly, the raters experienced differing levels of difficulty in identifying the respective sub-constructs in the students. That is, the 11 items in the instrument presented varying levels of difficulty of affirmation. Secondly, the engagement scores differed by gender (boys displaying lower levels of engagement) and whether favourite or least favourite subject was reported (favourite subjects displaying higher levels of engagement). The year of schooling of the student and the subject area (e.g. English, Mathematics, Science, and Society and Environment) did not account for variance in engagement scores. The implications of these findings are discussed.

Rekha Koul - One of the best experts on this subject based on the ideXlab platform.

Darrell L. Fisher - One of the best experts on this subject based on the ideXlab platform.

  • cultural background and students perceptions of science Classroom Learning environment and teacher interpersonal behaviour in jammu india
    Learning Environments Research, 2005
    Co-Authors: Rekha Koul, Darrell L. Fisher
    Abstract:

    This article reports research into associations between students’ cultural background and their perceptions of their teacher’s interpersonal behaviour and Classroom Learning environment. A sample of 1021 students from 31 classes in seven co-educational private schools completed a survey including the Questionnaire on Teacher Interaction (QTI), the What Is Happening In this Class? (WIHIC) and a question relating to cultural background. Statistical analyses showed that the Kashmiri group of students perceived their Classrooms and teacher interaction more positively than those from the other cultural groups identified in the study.

  • Monitoring constructivist Classroom Learning environments
    International Journal of Educational Research, 1997
    Co-Authors: Peter Charles Taylor, Barry J. Fraser, Darrell L. Fisher
    Abstract:

    The incorporation of constructivist and critical theory perspectives on the farming of the Classroom Learning environment led to the development of the Constructivist Learning Environment Survey (CLES). CLES enables researchers and teacher-researchers to monitor constructivist teaching approaches and to address key restraints to the development of constructivist Classroom climates. CLES assesses either student or teacher perceptions of Personal Relevance, Uncertainty, Student Negotiation, Shared Control, and Critical Voice. The p plausibility of the CLES was established in small-scale Classroom-based qualitative studies and its statistical integrity and robustness were validated in large-scale studies conducted in the USA and Australia.

Harrison Hao Yang - One of the best experts on this subject based on the ideXlab platform.

  • Exploring Students' Preferences Toward the Smart Classroom Learning Environment and Academic Performance
    2020 International Symposium on Educational Technology (ISET), 2020
    Co-Authors: Ningwen Feng, Harrison Hao Yang, Di Gong, Jinjun Dai
    Abstract:

    This study explores college students' (n=263) preferences toward the smart Classroom Learning environment and their academic performances. All students participated in the same course in the smart Classroom environment. The data were collected through the Preference Instrument of Smart Classroom Learning Environments and students' final exam. The results of the measurement of environmental preferences show that overall students are fond of the smart Classroom environment. Further, the results of the analysis of variance indicate that there are significantly differences in students' preferences for the smart Classroom among students in different levels of academic performance. The results reveal a "U" shape in students' academic performances and their preferences on the smart Classroom Learning environment. The middle-level academic performance students' preference toward the smart Classrooms Learning environment is notably less than high-level and low-level academic performance students. Based on the findings of this study, suggestions are made for researchers and practitioners.

  • Preferences toward the constructivist smart Classroom Learning environment: examining pre-service teachers’ connectedness
    Interactive Learning Environments, 2018
    Co-Authors: Harrison Hao Yang, Jason Macleod
    Abstract:

    The constructivist smart Classroom Learning environment is quickly emerging as an alternative Classroom model that integrates active Learning with advanced technology to improve learners’ socializa...

  • Understanding students’ preferences toward the smart Classroom Learning environment: Development and validation of an instrument
    Computers & Education, 2018
    Co-Authors: Jason Macleod, Harrison Hao Yang, Sha Zhu
    Abstract:

    Abstract This article presents the rationale for developing an instrument and initial evidence of validity and reliability in a higher education context. The 40-item instrument measures students' preferences toward the smart Classroom Learning environment from eight constructs that are characteristic for this environment, including: Student Negotiation, Inquiry Learning, Reflective Thinking, Ease of Use, Perceived Usefulness, Multiple Sources, Connectedness, and Functional Design. Data was purposely collected from a group of 462 college students enrolled in at least one smart Classroom course during the time of this study. The results showed no difference in preferences between genders and concluded that the instrument was a valid and reliable tool for measuring college students’ preferences toward a smart Classroom Learning environment.

Jason Macleod - One of the best experts on this subject based on the ideXlab platform.