Your search found 19995 results.

Descriptors:
Foreign Countries; Student Surveys; Qualitative Research; Statistical Analysis; Expectation; Elementary School Students; School Choice; Parent Attitudes; Intergroup Relations; Student Diversity; Learning Problems; Learning Processes; Friendship; Peer Relationship; Language of Instruction; Developing Nations; Outcomes of Education; Chinese; Code Switching (Language); Ethnic Diversity; Religious Cultural Groups; Religious Factors

Abstract:
This study surveys 200 Malay students enrolled in three Chinese primary schools in relation to three issues, i.e., parental choice of schooling, learning processes and inter-ethnic friendship patterns. The three issues are explored through a combination of quantitative and qualitative research methodologies. Parental expectations for their children's learning and academic outcomes emerge as the dominant factor influencing Malay enrollment in Chinese primary schools. Unfortunately, the Malay students are unable to meet these high expectations due to learning difficulties that stem from the lack of proficiency in the Chinese-medium of instruction, despite intervening measures by the school authorities. Their learning difficulties are also compounded by the lack of parental inputs as well as the limited use of code-switching by teachers. Meanwhile, the fostering of inter-ethnic friendships is impeded by ethnic differences, the rise of Islamic awareness and the increased numerical size of Malay students. However, there is a willingness among the Malay students to interact with the Chinese students through task-related activities, indicating that the fostering of inter-ethnic friendships needs to be guided by a convergence of interests. (Contains 4 tables.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Statistical Analysis; Foreign Countries; Usability; Social Influences; Geographic Information Systems; Geography Instruction; Knowledge Level; Secondary School Teachers; Teacher Motivation; Questionnaires; Teacher Attitudes; Models; High Schools

Abstract:
This article explores the adoption of geographic information system (GIS) knowledge and skills through in-service training for high school geography teachers in Taiwan. Through statistical analysis of primary data collected from a census of Taiwan's high school geography teachers, it explores what motivates these teachers to undertake GIS training. The design of the questionnaire was largely inspired by the technology acceptance model (TAM) and the social influence model (SIM). The former model postulates the influence of perceived usefulness (PU) and perceived ease of use (PEOU) of GIS on teachers' actual adoption of the technology. The latter, in contrast, postulates that teachers' usage of GIS is affected by their peers and their schools. Statistical findings indicate that PU and school support are important factors influencing teachers' adoption of GIS in Taiwan. (Contains 8 tables and 4 figures.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Effect Size; Test Bias; Item Analysis; Statistical Analysis; Sample Size; Research Design; Decision Making; Graphs; Scores

Abstract:
There are numerous statistical procedures for detecting items that function differently across subgroups of examinees that take a test or survey. However, in endeavouring to detect items that may function differentially, selection of the statistical method is only one of many important decisions. In this article, we discuss the important decisions that affect investigations of differential item functioning (DIF) such as choice of method, sample size, effect size criteria, conditioning variable, purification, DIF amplification, DIF cancellation, and research designs for evaluating DIF. Our review highlights the necessity of matching the DIF procedure to the nature of the data analysed, the need to include effect size criteria, the need to consider the direction and balance of items flagged for DIF, and the need to use replication to reduce Type I errors whenever possible. Directions for future research and practice in using DIF to enhance the validity of test scores are provided. (Contains 2 tables, 3 figures, and 1 note.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Factor Analysis; Social Justice; Psychometrics; Test Bias; Group Membership; Structural Equation Models; Culture Fair Tests; Error of Measurement; Statistical Analysis; Scores

Abstract:
Test fairness and test bias are not synonymous concepts. Test bias refers to statistical evidence that the psychometrics or interpretation of test scores depend on group membership, such as gender or race, when such differences are not expected. A test that is grossly biased may be judged to be unfair, but test fairness concerns the broader, more subjective evaluation of assessment outcomes from perspectives of social justice. Thus, the determination of test fairness is not solely a matter of statistics, but statistical evidence is important when evaluating test fairness. This work introduces the use of the structural equation modelling technique of multiple-group confirmatory factor analysis (MGCFA) to evaluate hypotheses of measurement invariance, or whether a set of observed variables measures the same factors with the same precision over different populations. An example of testing for measurement invariance with MGCFA in an actual, downloadable data set is also demonstrated. (Contains 4 tables, 1 figure, and 4 notes.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Structural Equation Models; Academic Achievement; Motivation; Self Determination; Medical Education; Medical Students; Gender Differences; Grade Point Average; Statistical Analysis; Goodness of Fit; Foreign Countries

Abstract:
Few studies in medical education have studied effect of quality of motivation on performance. Self-Determination Theory based on quality of motivation differentiates between Autonomous Motivation (AM) that originates within an individual and Controlled Motivation (CM) that originates from external sources. To determine whether Relative Autonomous Motivation (RAM, a measure of the balance between AM and CM) affects academic performance through good study strategy and higher study effort and compare this model between subgroups: males and females; students selected via two different systems namely qualitative and weighted lottery selection. Data on motivation, study strategy and effort was collected from 383 medical students of VU University Medical Center Amsterdam and their academic performance results were obtained from the student administration. Structural Equation Modelling analysis technique was used to test a hypothesized model in which high RAM would positively affect Good Study Strategy (GSS) and study effort, which in turn would positively affect academic performance in the form of grade point averages. This model fit well with the data, Chi square = 1.095, df = 3, p = 0.778, RMSEA model fit = 0.000. This model also fitted well for all tested subgroups of students. Differences were found in the strength of relationships between the variables for the different subgroups as expected. In conclusion, RAM positively correlated with academic performance through deep strategy towards study and higher study effort. This model seems valid in medical education in subgroups such as males, females, students selected by qualitative and weighted lottery selection. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Help Seeking; Asians; Surveys; Statistical Analysis; Foreign Students; College Students; Student Attitudes; Qualitative Research; Counseling

Abstract:
Using a mixed-methods survey design that was predominantly quantitative, this study explored Asian international students' willingness to seek counseling. Participants were 177 Asian international students recruited from a U.S. Midwestern University. After controlling for attitudes toward psychological help-seeking and past counseling experience, academic stress was significantly and positively related to willingness to seek counseling for academic problems. Qualitative data were also collected using one open-ended question in the survey: "What comes into your mind when you think about 'counseling' or 'mental health counseling'?" The qualitative analyses revealed positive perceptions of counseling as well as a personal reluctance to seek counseling. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Academic Achievement; Mathematics Achievement; High School Students; Grade 10; Grade 12; Recreational Activities; Reading Tests; Mathematics Tests; Reading Achievement; Computer Use; Video Games; Statistical Analysis; Longitudinal Studies; Correlation; Hierarchical Linear Modeling

Abstract:
Historically, the relationship between student academic achievement and use of computers for fun and video gaming has been described from a multitude of perspectives, from positive, to negative, to neutral. However, recent research has indicated that computer use and video gaming may be positively associated with achievement, yet these studies have focused on small intact and qualitative samples. The purpose of the present study is to examine the association between academic achievement in high school and student use of computers for fun and video gaming using the large nationally representative ELS:2002 sample of students in grade 10 in 2002 and an independent effects two-level hierarchical linear model. Our results indicate that both student use of computers for fun and moderate levels of video gaming were positive and significant on cross-sectional reading and mathematics achievement assessments in high school, controlling for multiple covariates of achievement, but were not related to growth in mathematics from grade 10 to grade 12. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Academic Achievement; Item Analysis; Undergraduate Students; Goal Orientation; Prediction; Futures (of Society); Pretests Posttests; Scores; Reading Tests; Correlation; Statistical Analysis; Profiles

Abstract:
In this study, undergraduate students provided confidence ratings to predict future performance in answering questions drawn from the text before reading the text, after reading the text and after rereading the text. Self-reports of achievement goal orientations during reading and posttest scores were also collected. Student's calibration index was the comparison between their predicted posttest performance and actual performance in the posttest. Correlational analyses did not reveal any statistically detectable relationships between self-reported goal orientations and monitoring accuracy, except that bias scores were marginally related to goal orientations. Further cluster analyses and analyses of variance (ANOVA) also showed that student's multiple goal profiles failed to clearly differentiate the groups in terms of their calibration accuracy, yet performance-approach goals did distinguish overconfident from underconfident students. Plausible reasons for the finding were provided and implications for future research were also discussed. (Contains 3 tables.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Academic Failure; Adolescents; Foreign Countries; High School Students; Student School Relationship; Academic Achievement; Role; Prevention; Longitudinal Studies; Correlation; Attachment Behavior; Statistical Analysis; Learner Engagement

Abstract:
School engagement, or the extent to which students are involved in, attached and committed to the academic and social activities in school, plays a prominent role in preventing academic failure, promoting competence, and influencing a wide range of adolescent outcomes. Although the multidimensional nature of school engagement is well-recognized, how the three purported parts of the construct work together is largely unknown. By using data from the longitudinal, 4-H study of Positive Youth Development, involving a sample of 1,029 adolescents (67.7% female; mean age at Grade 9 = 14.92 years; 74.4% of participants were European American, 5.2% were Latino/a, 7.3% were African American), the current study examined the interrelationships of behavioral, emotional, and cognitive aspects of school engagement over three years in adolescence (Grades 9-11). We used autoregressive lagged effects models to assess the relationships among the three engagement constructs. Results indicated that behavioral and emotional engagement were related bidirectionally (each variable was a basis and an outcome of the other). In addition, behavioral engagement influenced cognitive engagement (but the reverse of this relation was not found). Implications for future research are discussed. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website

Descriptors:
Student Attitudes; Questionnaires; Construct Validity; Predictive Validity; Educational Environment; High School Students; Statistical Analysis; Validity; Educational Change; Social Capital; Bullying; Well Being; Academic Achievement

Abstract:
This article describes the development and validation of a six-scale survey to assess school climate in terms of students' perceptions of the degree to which they feel welcome and connected, together with a scale to assess students' perceptions of bullying. The development of each survey involved a multi-stage approach, including: 1) an extensive review of research related to school climate to identify components that can be considered important for effective schools made up of diverse students; 2) elucidating the scales identified in step one; and 3) writing individual items within the scales. Items from previously validated questionnaires were examined and, if appropriate, adapted. We used Trochim and Donnelly's (2006) framework for construct validity to guide the validation of the new questionnaire. When the questionnaire was administered to a sample of 4067 high school students from eight schools, various statistical analyses ensured the questionnaire's discriminant, convergent, concurrent and predictive validity. (Contains 5 tables and 1 figure.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

Related Items: Show Related Items

Full-Text Availability Options:

More Info:
Help | Tutorial Help Finding Full Text |  More Info:
Help Find in a Library |  Publisher's website