quantitative methods teaching: a collaborative learning approach - sarah keast, fangya xu and...
DESCRIPTION
This is a draft of the presentation that will be given at the HEA Social Sciences annual conference - Teaching forward: the future of the Social Sciences. For further details of the conference: http://bit.ly/1cRDx0p Bookings open until 14 May 2014 http://bit.ly/1hzCMLR or [email protected] ABSTRACT This paper explores the development of a programme of learning to enable first year undergraduate students to develop their quantitative methods knowledge and skills. The plan is to dispense with traditional lectures, replacing them with discussion sessions which promote collective learning. This will be facilitated through a set of customised video lectures created using the TEDEd website. The course will combine an innovative blend of teaching and assessment approaches including learning through teaching, peer assessment, and viva voce with the aim of engendering a culture of collaborative learning. This paper reflects upon the development and implementation of this study programme.TRANSCRIPT
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Quantitative Methods Teaching
A Collaborative Approach
Dr Sarah Keast, Dr Fangya Xu, Panagiotis Tziogkidis
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Background Motivation The Literature The Plan Resources An example
Introduction
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Economics Group◦ Faculty of Business
Students◦ Average cohort 110◦ No post 16 mathematics qualification required
Programmes◦ BSc Economics (7 separate programmes in total)◦ Core second year Econometrics and final year electives in
mathematical economics and economic modelling Module
◦ Core for all Economics programmes◦ 20 credits◦ Mathematical and statistical modelling
Background
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Motivation Traditional lecture/tutorial format not
effective for teaching QM Lack of engagement amongst some
students Increased size of cohort More efficient use of staff resources Perceived decline in quantitative skills of in-
coming students
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Economics is less popular among disciplines in the NSS, especially with respect to assessment and feedback
Recent trends in teaching and learning include:◦ Peer learning◦ Problem based approaches◦ Use of online resources to facilitate independent
reading
Literature
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ETL project in economics: the traditional lecture-tutorial mode seems to fall apart
Constructive alignment: Biggs (1996)◦ … but also align with students: Reimann (2004)
Threshold concepts for teaching QM: Meyer and Land (2003)
Problem based approaches and “learning by doing”: Kolb (1984), Barnett (2009)◦ … particularly good for QM (Aliaga et al., 2012)
Student learning in economics
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20 %
10 %
5%
30 %
50 %
75 %
90 %
Lecture
Reading
Audio Visual
Demonstration
Group Discussion
Practice
Teaching others
Retention rate The learning pyramid
Source: National Training Laboratories, Bethel, Maine
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“To teach is to learn twice” - Whitman and Fife (1988)
The “learning cell”: Goldschmid (1970) Many benefits but many challenges: Boud
et al. (2001), Topping (2005) Assessment needs to be well-thought: Boud
et al. (1999) Recent examples: Herrmann (2013)
Peer learning
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Learning opportunities◦ Resource based learning: Video ‘lectures’ ◦ Learning through teaching◦ Experiential learning
Assessment and feedback◦ Peer assessment and critique◦ Online self-assessment with immediate automatic
feedback◦ Mini viva assessed by academic staff with specific
feedback◦ Consultancy style report and presentation with
authentic feedback
The Plan
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A series of resource booklets consisting of the following material:◦ Background documents with key concepts and
intended learning outcomes ◦ TED-Ed: build an online lesson using TED-Ed and
YouTube resources http://ed.ted.com/lessons?category=business-economics
◦ Mathematical for Economics: enhancing Teaching and Learning (METAL) http://www.metalproject.co.uk/
◦ Questionmark-Perception (QMP) and MyMathLab are used for self-assessment/formal assessment
Resources
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Example: How to Calculate Equilibrium Price and
Quantity
http://ed.ted.com/activity/lessons?lesson=EJuCkuSP&state=updateShare the lesson with students and ask them toWatch-Think-Dig deeper-Discuss-And Finally
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Teaching QM in economics is challenging We propose a blend of collaborative
learning and resources Obvious benefits but pitfalls that must be
avoided
Summary