Motivation and Learning Strategies in EMI versus non-EMI students 1 Challenges and Opportunities of the International Classroom: A one-day seminar 4th April 2016 Mª José Rivero-Menéndez (CUNEF) Elena Urquía-Grande (UCM) Mª Mar Camacho-Miñano (CUNEF) Pilar López-Sánchez (UFV)
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Motivation and Learning Strategies
in EMI versus non-EMI students
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Challenges and Opportunities of the International Classroom: A one-day seminar
4th April 2016
Mª José Rivero-Menéndez (CUNEF) Elena Urquía-Grande (UCM)
Mª Mar Camacho-Miñano (CUNEF) Pilar López-Sánchez (UFV)
Structure
• Motivation
• Objectives
• Context
• Sample description & Methodology
• Findings discussion
• Conclusions
• Limitations and Future research
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Motivation
• The internationalization of the Higher Education and the XXIst century has economic and social needs.
• International academic and professional talent attraction and retention: English as the medium of communication.
• Higher Education Institutions and lecturers need to know about differences in motivation and learning strategies in the use of English as a Medium of Instruction (EMI) students.
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Objectives
• The objectives of this paper are:
– First, to analyse if the English as medium of instruction
determine students’ learning strategies and their motivation.
– Second, to evidence whether there is a link between motivated students and their learning strategies.
– A survey designed out of the Motivation and Strategies for Learning Questionnaire (MSLQ) is carried out in a sample of 64 undergraduate students of Business Administration Degree taught in English (32) and in Spanish (32) at the UCM.
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• There has been much research about the Motivated and Learning Strategies Questionnaire (MLSQ) created by Pintrich et al. (1991) after it has been improved by educational psychologists and researchers (Mckeachie & Pintrich, 1986; Pintrich and De Groot, 1990; Pintrich et al., 2001; Pintrich et al., 2003; Duncan & Mckeachie, 2005)
• The MLSQ is a Likert-scaled instrument that was designed to assess motivation and use of learning strategies of College students.
• The section about motivation is divided in three main areas: firstly value including intrinsic and extrinsic goal orientation and task value, the expectancy measured by control beliefs about learning and self-efficacy and, thirdly, the affection or test anxiety.
• The learning strategies section is comprised of nine scales which can be distinguished as cognitive, meta-cognitive, and resource management strategies.
– The Cognitive strategies scales include rehearsal, elaboration, organization, and critical thinking.
– Meta-cognitive strategies are assessed by one large scale that includes planning, monitoring, and regulating strategies.
– Resource management strategies include managing time and study environment; effort management, peer learning, and help-seeking.
• All scale reliabilities are robust, and confirmatory factor analyses demonstrated good factor structure.
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Context (I)
Context (II) Therefore several authors have used part of this questionnaire to analyse some
parts within student academic performance research (Bong 2001; Campbell 2001; Loyens et al., 2008)
In addition, the instrument shows reasonable predictive validity to the actual course performance of students demonstrated by several authors (Artino, 2005; Boekaerts and Corno, 2005; Cardozo, 2008)
Other empirical studies using MLSQ with different aims compare motivation and
learning strategies towards different teaching resources Case vs lecture (Barise, 2000);
Multimedia (Liu, 2003)
Computer based versus web based (Eom & Reiser 2000)
Rotation Method: Varimax with Kaiser Normalization.a,b
a. Rotation converged in 15 iterations.
b. Only cases for which subject = 1 are used in the analysis phase.
Findings Discussion (II) ANOVA
Motivation is higher in EMI students compared with non-EMI
Relying in learning basic concepts (6,16 vs 5,38)
Understanding basic concepts (5,13 vs 4,50)
Performing highly in class (5,75 vs 4,65)
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Findings Discussion (III)
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ANOVA Instead Learning Strategies are similar in EMI and non-EMI students except for: - Effort where
- EMI students 3,06 versus non-EMI 3,56 (lowest values)
- Time-Study Management where
- EMI students 5,69 versus non-EMI 4,09
Findings Discussion (III)
• Correlation Matrix between motivation and learning strategies with no distinction between EMI and non-EMI students – Motivation correlates with Time-Study Management (TSME) and with
a. Dependent Variable: REGR factor score 1 for analysis 1
Conclusions (I)
• The eight questions about motivation integrated into a variable measuring total motivation in self-efficacy for learning and performance (MSLP)
• The thirty two questions about learning strategies integrated into eight factors: effort, self-regulation, time-study management, methodology focus difficulty and perseverance.
• EMI students have higher motivation than non-EMI although there are not significant differences in learning strategies – EMI students have higher motivation in learning and understanding basic
concepts correctly and performing well in class
– EMI students have better learning strategies when self-regulating, managing their time-studies and their effort (although lowest values in all students)
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• Students’ motivation correlates highly with self-regulating learning strategies as time-study management and perseverance, in line with Pintrich, 2003, without distinction between EMI and non-Emi students – More motivated students manage better their time studies
– More motivated students are more perseverant
• Total motivation in self-efficacy for learning and performance can be explained by the students’ PAU (mark achieved in the global exam to study in Higher Education), Time-study management and Perseverance
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Conclusions (II)
Conclusions (III)
• There is a learning strategy about students’ focus capacity that should be encouraged
• Motivation and learning strategies are not static – Motivation is dynamic
– Learning strategies can be developed
• Lecturers can be aware of the students learning strategies, such as self regulation and time management at home, in order to improve teaching procedures and deep learning
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Limitations and Future Research
• Limitations
– Small sample
– Only one public university
– Only one subject
– Only one academic year
• Future research
– Enlarge the sample and compare data from public and private universities