Validation of a tool for predicting Iranian engineering student success in elearning
E-learning systems are developing tremendously all over the world. More than one thousand institute have been accepted this method of teaching and learning parallel with their conventional system. In this rapid development phase, institute encountered with some problem of early attrition, withdraw,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | fas |
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Iran Academy of Science
2013-06-01
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| Series: | آموزش مهندسی ایران |
| Subjects: | |
| Online Access: | https://ijee.ias.ac.ir/article_2965.html?lang=en |
| _version_ | 1797796011624628224 |
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| author | Mohammad Ali Rostami Nejad Naser Mazini Ali Delavar Daryosh Norouzi |
| author_facet | Mohammad Ali Rostami Nejad Naser Mazini Ali Delavar Daryosh Norouzi |
| author_sort | Mohammad Ali Rostami Nejad |
| collection | DOAJ |
| description | E-learning systems are developing tremendously all over the world. More than one thousand institute have been accepted this method of teaching and learning parallel with their conventional system. In this rapid development phase, institute encountered with some problem of early attrition, withdraw, failure and dropout. So increasing e-learner success rate is one of the main and common concerns of all e-leaning centers .Although considering technological, infrastructural, content related, teacher and support system factors are undoubtedly very important in this regard, but it is believed that e-learner related factors has also a critical role. The goal of this study is developing and validation of a tools to predict e-learner's success rate. Instrument such as Online Distance Learner Survey (ODLS),Test of Online Learning Success(TOOLS), Tertiary Students’ Readiness for Online Learning(TSROL) were reviewed in the literature. To achieve the goal of the study, all item of the pre mentioned instrument were analyzed. Then a questioner is developed according to the literature and authors experience in IUST e-learning centre. In this step some subscales and items that are not important for e-learner success removed from scale. The initial scale is constructed with 67 items. In the next step 290 e-learners from IUST e-learning center have been selected randomly and asked to describe themselves in reference to a 5-point Likert-type scale, with anchors ranging from 1 (strongly disagree) to 5 (strongly agree). Exploratory factor analysis with varimax rotation where used to study constructs validity of the before mentioned tool. The result revealed that eleven-factor solution with Eignevalue over than one can count 62% variance of e-learner success construct. Iin this stage 24 items where excluded due to lack of factor load in any eleven-factors. Another intention of this study is to test reliability of the developed tool. The reliability of the questionnaire found satisfactory, with a Cronbach alpha of α=0.84 for the entire set of questioner. Although the developed questionnaire have construct validity and is reliable but the predictive validity has a crucial importance for authors so it is continued with using multiple regression with inter method . The average score of items that is related to each factor were calculated and enterd as a predictor into linear regression. The finding showed that eleven-factor can predict 14% valiance of e-learner GPA in our sample. Comparing this tool with others, it shows that it is reliable and has predictive validity that can be used for Iranian engineering education institute. Finally the paper conclude findings and present some recommendation to use this toll effectively. |
| first_indexed | 2024-03-13T03:26:42Z |
| format | Article |
| id | doaj.art-caf931f4fa4a4e33bbe43bb294eaf504 |
| institution | Directory Open Access Journal |
| issn | 1607-2316 2676-4881 |
| language | fas |
| last_indexed | 2024-03-13T03:26:42Z |
| publishDate | 2013-06-01 |
| publisher | Iran Academy of Science |
| record_format | Article |
| series | آموزش مهندسی ایران |
| spelling | doaj.art-caf931f4fa4a4e33bbe43bb294eaf5042023-06-25T08:44:59ZfasIran Academy of Scienceآموزش مهندسی ایران1607-23162676-48812013-06-01155711313210.22047/ijee.2013.2965Validation of a tool for predicting Iranian engineering student success in elearningMohammad Ali Rostami Nejad0Naser Mazini1Ali Delavar 2Daryosh Norouzi 3PhD Candidate of ATU University, Tehran, Iran.Assistant Professor, School of Computer, IUST University. Tehran, Iran Professor ,School of Psychology and Education, ATU University, Tehran, Iran.Associate Professor , School of Psychology and Education, ATU University, Tehran, Iran.E-learning systems are developing tremendously all over the world. More than one thousand institute have been accepted this method of teaching and learning parallel with their conventional system. In this rapid development phase, institute encountered with some problem of early attrition, withdraw, failure and dropout. So increasing e-learner success rate is one of the main and common concerns of all e-leaning centers .Although considering technological, infrastructural, content related, teacher and support system factors are undoubtedly very important in this regard, but it is believed that e-learner related factors has also a critical role. The goal of this study is developing and validation of a tools to predict e-learner's success rate. Instrument such as Online Distance Learner Survey (ODLS),Test of Online Learning Success(TOOLS), Tertiary Students’ Readiness for Online Learning(TSROL) were reviewed in the literature. To achieve the goal of the study, all item of the pre mentioned instrument were analyzed. Then a questioner is developed according to the literature and authors experience in IUST e-learning centre. In this step some subscales and items that are not important for e-learner success removed from scale. The initial scale is constructed with 67 items. In the next step 290 e-learners from IUST e-learning center have been selected randomly and asked to describe themselves in reference to a 5-point Likert-type scale, with anchors ranging from 1 (strongly disagree) to 5 (strongly agree). Exploratory factor analysis with varimax rotation where used to study constructs validity of the before mentioned tool. The result revealed that eleven-factor solution with Eignevalue over than one can count 62% variance of e-learner success construct. Iin this stage 24 items where excluded due to lack of factor load in any eleven-factors. Another intention of this study is to test reliability of the developed tool. The reliability of the questionnaire found satisfactory, with a Cronbach alpha of α=0.84 for the entire set of questioner. Although the developed questionnaire have construct validity and is reliable but the predictive validity has a crucial importance for authors so it is continued with using multiple regression with inter method . The average score of items that is related to each factor were calculated and enterd as a predictor into linear regression. The finding showed that eleven-factor can predict 14% valiance of e-learner GPA in our sample. Comparing this tool with others, it shows that it is reliable and has predictive validity that can be used for Iranian engineering education institute. Finally the paper conclude findings and present some recommendation to use this toll effectively. https://ijee.ias.ac.ir/article_2965.html?lang=ene-learner student characteristics dropout academic success engineering |
| spellingShingle | Mohammad Ali Rostami Nejad Naser Mazini Ali Delavar Daryosh Norouzi Validation of a tool for predicting Iranian engineering student success in elearning آموزش مهندسی ایران e-learner student characteristics dropout academic success engineering |
| title | Validation of a tool for predicting Iranian engineering student success in elearning |
| title_full | Validation of a tool for predicting Iranian engineering student success in elearning |
| title_fullStr | Validation of a tool for predicting Iranian engineering student success in elearning |
| title_full_unstemmed | Validation of a tool for predicting Iranian engineering student success in elearning |
| title_short | Validation of a tool for predicting Iranian engineering student success in elearning |
| title_sort | validation of a tool for predicting iranian engineering student success in elearning |
| topic | e-learner student characteristics dropout academic success engineering |
| url | https://ijee.ias.ac.ir/article_2965.html?lang=en |
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