International Journal of Physical and Social Sciences

  • Year: 2015
  • Volume: 5
  • Issue: 7

Investigate the relationship between interpersonal communication with learning approaches

  • Author:
  • Hamideh Beyraghi1, Dr:: Fazlollahyazdani2
  • Total Page Count: 8
  • DOI:
  • Page Number: 516 to 523

1Department of Curriculum Development, Meymeh Branch, Islamic Azad University, Meymeh, Iran

2Faculty Member, Department of Curriculum development, Meymeh Branch, Islamic Azad University, Meymeh, Iran

Abstract

This study examined the relationship between students’ perception of the quality of the curriculum of Islamic Azad University Meymeh teaching and learning approach chosen by them. The purpose of the study, and application of the method is descriptive correlational. The population of this study curriculum, all students of Islamic Azad University were the Meymeh By using the simple random sampling. And the formula for determining the sample size of 110 students (59 males and 51 females) as the sample is taken. To measure students’ approaches to learning and study skills and learning approaches questionnaire Antvysl and Ramsdn (2000) is used. To analyze the data, correlation and regression analysis were used. Results indicate that the relationship between the perception of the quality of teaching comprise individual components, reflective thinking, classroom interaction and learning with profound learning strategy with positive and negative surface and meaningful learning. Also support deep learning and positive relationship with learning strategy is negative and significant. Relationship led to deep learning, positive and negative and significant strategic learning. Empathy is also a significant negative correlation with the level of learning. Meanwhile, the perception of the quality of teaching, about 27 percent of the variation in deep learning, learning level and 34% to 21% of the variation explained by changes in strategic learning, which is a significant amount.

Keywords

Quality of teaching, Learning approach, Deep learning, Surface learning, Strategic Learning