Acquisition of Higher Order Knowledge by a Dynamic Modeling Environment Based on the Educational Concept of Self-Regulated Learning

2013 ◽  
pp. 393-416
Author(s):  
Stefanie A. Hillen
Keyword(s):  
Dynamic Modeling ◽  
Higher Order ◽  
Self Regulated Learning ◽  
Modeling Environment ◽  
Educational Concept ◽  
Regulated Learning

scholarly journals The Effectiveness of E-Module on Buffer Solutions to Improve Students' Higher-Order Thinking Skills and Self-Regulated Learning

2021 ◽  
Vol 6 (2) ◽  
pp. 254-266
Author(s):  
Alfiyani Lestari ◽  
Sri Atun
Keyword(s):  
Higher Order Thinking ◽  
Thinking Skills ◽  
Higher Order ◽  
Learning Cycle ◽  
Buffer Solution ◽  
Higher Order Thinking Skills ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Before And After ◽  
The Difference

This study aims to determine the difference between Higher Order Thinking Skills (HOTS) and Students Self Regulated Learning (SRL) before and after using e-module based on the 7E (elicit, engage, explore, explain, elaborate, evaluate, and extend) learning cycle on the buffer solution material, and to determine the percentage of its effectiveness. The research use a quasi experiment with one-group pretest-posttest design. The subjects of this research were students of natural science 11th grade in one of senior high schools in Yogyakarta. The instrument used were test in the form of HOTS pretest-posttest description question and non-test in the form of self-regulated learning questionnaire. The data analysis technique used is Hotteling's T2 test. The results showed that the significance value was 0.000 < = 0.05, then H0 was rejected. There were differences in students' HOTS and SRL before and after using e-module based on the 7E learning cycle. The effectiveness of using e-module show by HOTS and SRL simultaneously (36.8%), HOTS (25.2%), and SRL (20.5%).

Development of the Teacher Attitudes Towards Self-Regulated Learning Scale

2018 ◽  
Vol 34 (3) ◽  
pp. 193-205 ◽  
Author(s):  
Julia Steinbach ◽  
Heidrun Stoeger
Keyword(s):  
Factor Analysis ◽  
Primary School ◽  
Factor Structure ◽  
Concurrent Validity ◽  
Binary Logistic Regression ◽  
Affective Component ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Teachers Attitudes ◽  
Development And Validation

Abstract. We describe the development and validation of an instrument for measuring the affective component of primary school teachers’ attitudes towards self-regulated learning. The questionnaire assesses the affective component towards those cognitive and metacognitive strategies that are especially effective in primary school. In a first study (n = 230), the factor structure was verified via an exploratory factor analysis. A confirmatory factor analysis with data from a second study (n = 400) indicated that the theoretical factor structure is appropriate. A comparison with four alternative models identified the theoretically derived factor structure as the most appropriate. Concurrent validity was demonstrated by correlations with a scale that measures the degree to which teachers create learning environments that enable students to self-regulate their learning. Retrospective validity was demonstrated by correlations with a scale that measures teachers’ experiences with self-regulated learning. In a third study (n = 47), the scale’s concurrent validity was tested with scales measuring teachers’ evaluation of the desirability of different aspects of self-regulated learning in class. Additionally, predictive validity was demonstrated via a binary logistic regression, with teachers attitudes as predictor on their registration for a workshop on self-regulated learning and their willingness to implement a seven-week training program on self-regulated learning.

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