Seminars and Events

All events are held at 15 Norham Gardens, Oxford OX2 6PY unless otherwise stated.

All are welcome to those indicated as ‘public seminars’ in parentheses after the title. These are held on Monday evenings and there is no need to book. If you are coming from outside the Department and would like to attend any of the other seminars or events, please contact the convener(s) beforehand.
Click on the title of the event for further information.

Evidence-informed educational practice for children in care

Webinar hosted by the Rees Centre

10 February 2015 16:30 - 16:30
Webinar

Conveners: Alun Rees and Lucy Wawrzyniak, Visiting Research Fellows, the Rees Centre.

For further information see the Rees Centre events page

Parenting practices predictive of children’s self-regulation development: Evidence from the UK

Alex Baron

27 April 2015 12:15 - 13:45
Seminar Room E

Conveners: Dr Lars-Erik Malmberg, Quantitative Methods Hub

Abstract:
Children’s ability to exercise self-regulation is a key predictor of academic, behavioral, and life outcomes, but the developmental dynamics of children’s self-regulation in early childhood are not yet adequately understood. Using data drawn from the Millennium Cohort Study in the UK, we investigate how harsh and sensitive parenting practices affect the development of children’s self-regulation from the age of 3 to 7, as well as how children’s self-regulation reciprocally affects parenting practices. The results from a latent growth analysis indicate that harsh parenting predicts lower initial self-regulation level, whereas sensitive parenting predicts a higher initial level. Moreover, a bidirectional relationship was observed whereby early harsh parenting predicted lower subsequent self-regulation, which then predicted higher harsh parenting and vice versa.

What is educational neuroscience? (public seminar)

Professor Dorothy Bishop, Department of Experimental Psychology

27 April 2015 17:00 - 18:30
Seminar Room A

Convener: Professor Victoria Murphy, Applied Linguistics Research Group

Introduction to structural equation models (SEM)

**THIS COURSE IS FULLY BOOKED**

05 May 2015 09:00 - 16:30

The concept of a latent construct is central in the social sciences. A latent construct is a not directly observed phenomenon (e.g., attitude, socioeconomic status) that we can model using manifest (observed) variables (e.g., survey and questionnaire responses, observation scores), by partitioning out residual (i.e., uniqueness, error variance). The structural equation model (SEM) is divided into two parts. In the measurement part of the model, we can inspect whether manifest variables measure the constructs they are intended to measure. This model is called confirmatory factor analysis (CFA) which allows the researcher to test whether an a priori model fits data, and whether this also holds across multiple groups. If measurement is satisfactory, the relationships between constructs can be estimated in the structural part of the SEM. Complex relationships between manifest variables and/or latent constructs can be tested in path-models not possible to specify in the multiple regression framework. During the course we will cover worked examples relevant for educational, psychological and social sciences. Participants need to understand the basics of multiple regression, or other relevant multivariate statistics.

Contents: 
9-10:45 Introduction: Basic concepts, models and measurement. From multiple regression to path-models using manifest variables.
11-12:30 Observed (manifest) variables and unobserved (latent) constructs. Specification of measurement models for testing quality of measurement, using continuous and dichotomous manifest variables. Goodness-of-fit indices.
13-14:45 Relationships between latent constructs. Specifying structural models to include directional (regression) paths between latent constructs.
15-16:30 Multiple group designs and testing of invariance constraints. Modelling intercepts and latent means.

Registration: *COURSE FULLY BOOKED* 

Multilevel models for educational data

Instructors: Dr. Daniel Caro, Dr. Lars-Erik Malmberg and Lorena Ortega

07 May 2015 09:00 - 16:00
IT Room, Manor Road Building, Manor Road, Oxford, OX1 3UQ

This one-day workshop will introduce MLM, with a focus on applications and interpretation of results, and provide an overview of MLM for change to model longitudinal data and advanced MLM for non-hierarchical data structures (i.e., cross- classified and multiple membership models). Lectures will be combined with hands-on practical exercises using the software package SPSS. Participants need to understand the basics of multiple regression, or other relevant multivariate statistics.

Contents:
09:00-10:30 Introduction to MLM
10:45-12:00 MLM in SPSS
12:30-14:00 MLM for change
14:15-16:00 Advanced MLM: Cross-classified and Multiple membership models

Course fee:
Oxford University Participant (Students, Staff): No charge
Other Students: £30
External Other: £100
The course fee includes access to training sessions/events, event materials, lunch and refreshments. The fee does not include accommodation or travel

Registration:
Oxford University participants should register via Weblearn. Browse by Department and select Education.
Other students and external participants please complete the registration form and return by email to lorena.ortega@education.ox.ac.uk

ESRC Student Bursaries:

ESRC student bursaries are available to postgraduate students from Higher Education Institutions outside Oxford to provide up to £120 per day financial assistance toward the cost of attending the course. Students will also be able to claim reasonable travel costs within the UK to Oxford, plus reasonable accommodation costs up to £100 per night for the duration of the course. Students must pay upfront for the course and then claim costs back after they have attended, providing receipts for all expenses.

Please note: You must be a postgraduate research student at a UK Higher Education Institution to be eligible for bursary funding.

If you would like to apply for an ESRC student bursary please complete the ESRC bursary application form and return it by email to lorena.ortega@education.ox.ac.uk together with your registration form.

Are there distinctive clusters of higher and lower status universities in the UK?

Vikki Boliver, University of Durham

11 May 2015 12:15 - 13:45
Seminar Room E

Conveners: Dr Lars-Erik Malmberg, Quantitative Methods Hub

Abstract:
In this paper I analyse publicly available data on the research activity, teaching environment, economic resources, academic selectivity and social mix of UK universities to explore how the differentiation of UK universities is structured. In 1992 the binary divide between universities and polytechnics was dismantled to create a nominally unitary system of higher education for the UK. However, the following year saw the publication of the first UK university rankings, and the year after that saw the formation of the Russell Group of self-proclaimed "leading" universities. This paper asks whether UK universities are spread out along a fine-grained linear hierarchy of the sort brought to mind by university rankings, or whether there are distinctive clusters of higher and lower status universities as suggested by the existence of university mission groups such as the Russell Group. In particular the paper asks whether the Russell Group of universities can be said to form a distinctive cluster of leading universities.

Evaluating effectiveness of education systems and instructional approaches with PISA data

Daniel Caro

18 May 2015 12:15 - 13:45
Seminar Room E

Conveners: Dr Lars-Erik Malmberg, Quantitative Methods Hub

Abstract:
This research uses the dynamic model of educational effectiveness to investigate effectiveness-enhancing factors with data from PISA 2012. PISA 2012 included information on teacher’s instructional strategies, class management, and school climate reported by students. The dynamic model postulates interactions between effective practices and student, class, and school characteristics as well as non-linear associations with student outcomes. The presentation will explore some of these interactions and non-linear effects within and between education systems.

The comprehensive school (Die Gesamtschule) - the anatomy and pathology of secondary school reform in Germany and Austria

Karl Heinz Gruber, University of Vienna

18 May 2015 17:00 - 18:30
Seminar Room A

Convener: Professor Ian Menter, Teacher Education and Professional Learning research group

Advanced structural equation models (SEM): longitudinal and multilevel SEM

Instructor: Dr. Lars-Erik Malmberg

19 May 2015 09:00 - 16:30
IT Room, Manor Road Building, Manor Road, Oxford, OX1 3UQ

This follow-up of the introduction to SEM (May 5th, details above) is an advanced course in which we focus on SEM for longitudinal and multilevel data. Prospective longitudinal data is usually collected over longer periods of time (e.g., yearly) while intensive longitudinal is gathered within shorter time-spans (e.g., numerous times a day). Both cross-sectional and longitudinal data can be collected applying a nested structure (e.g., students in classrooms, parents in families, time-points in persons). Using SEM we can model repeated latent constructs over time, or across hierarchical levels net of measurement error. In this course we will start off with analysis of models in which the time-structure is explicit. We will then introduce multilevel structural equation models (MSEM), in which we specify models in which time is not explicitly modelled. We will end with models in which the time-structure is explicit in multilevel data.

During the course we will cover worked examples relevant for educational, psychological and social sciences. Participants need to understand the basics of multiple regression, other relevant multivariate statistics, and have some exposure to either multilevel regression or SEM.

Contents:
9-10:45 Quick introduction to SEM; Modelling longitudinal data using repeated constructs or time-varying constructs; Models with and without mean-structure; Autoregressive models with latent constructs; Reciprocal effects; The latent change model (for experimental designs).
11-12:30 The latent growth model: Coding of time; Error structures; The autoregressive latent trait model;
13-14:45 Multilevel factor structures; Multilevel structural models (MSEM) with covariates; Centering and contextual effects; Contrasting examples using time-points in students, students in classrooms, and parents in families.
15-16:30 Models for intensive longitudinal data using “individuals as their own controls”; Fixed and random effects models; cross-level interaction effects; Models for explicit time: dynamic factor analysis and intraindividual variability.

Course fee:
Oxford University Participant (Students, Staff): No charge
Other Students: £30
External Other: £100
The course fee includes access to training sessions/events, event materials, lunch and refreshments. The fee does not include accommodation or travel.

Registration:
Oxford University participants should register via Weblearn. Browse by Department and select Education.
Other students and external participants please complete the registration form and return by email to lorena.ortega@education.ox.ac.uk

ESRC Student Bursaries:

ESRC student bursaries are available to postgraduate students from Higher Education Institutions outside Oxford to provide up to £120 per day financial assistance toward the cost of attending the course. Students will also be able to claim reasonable travel costs within the UK to Oxford, plus reasonable accommodation costs up to £100 per night for the duration of the course. Students must pay upfront for the course and then claim costs back after they have attended, providing receipts for all expenses.

Please note: You must be a postgraduate research student at a UK Higher Education Institution to be eligible for bursary funding.

If you would like to apply for an ESRC student bursary please complete the ESRC bursary application form and return it by email to lorena.ortega@education.ox.ac.uk together with your registration form.

Economic returns to A level mathematics

Professor Andrew Noyes and Dr Mike Adkins, University of Nottingham

19 May 2015 16:30 - 18:00
Seminar Room G

Convener: Dr Jenni Ingram, Mathematics Education Research Group

Abstract
In 1999, Peter Dolton and Anna Vignoles first published their econometric analysis of the 1958 National Child Development Study which showed that A level mathematics was unique in having a wage premium of 7-10% at age 33, for that sample of the population.  In our Nuffield-funded project, Rethinking the Value of Advanced Mathematics Participation, we have replicated the original research and then repeated the analysis with the later 1970 British Cohort Study, using Bayesian modelling and multiple imputation techniques.  In this session we will present the findings from this analysis to show that there appears to  be a sustained ‘return’ to A level mathematics over time, although why this might be is not entirely clear.  Secondly, we present an analysis of how the original research has been taken up by policymakers and what Stephen Ball and Sonia Exley term policy interlockers.  Thirdly, we will set out how this work package fits into the wider project and how the findings raise further questions and new avenues of inquiry.

Creating opportunity for digital participation: Integrating computer science in the primary curriculum

Dr Caitlin McMunn Dooley, Georgia State University

27 May 2015 17:00 - 18:30
Seminar Room G/H

Convener: Dr Rebecca Eynon, Learning and New Technologies Research Group

Abstract:
Focusing on design thinking and integrated curriculum design, this research talk will describe an investigation of how to integrate computer science and online literacies into primary classroom settings. Primary computer science is one way to invite learners as digital participants. The study described here will demonstrate how one school is changing curriculum to encourage digital participation. Theories about participatory digital practices, constructionism, and empowering/emancipatory education offer teachers a foothold for curricular innovation. However, new theories about how to engage learners (and teachers) in meaningful and meaning-making digital practices continue to develop as teachers take up and use these theories in the contexts of schools and learning.

About the speaker:
Caitlin McMunn Dooley, Ph.D., is an Associate Professor at Georgia State University in the US. Her research focuses on digital literacies, early literacy development, and teacher development.

Studying how psychological treatments work using structural equation modelling.

Katu Sivyer

01 June 2015 12:15 - 13:45
Seminar Room E

Conveners: Dr Lars-Erik Malmberg, Quantitative Methods Hub

 

Higher education expansion and social mobility: Is this the UK government's vision?

Dr Susan James, Deputy director of SKOPE

01 June 2015 17:00 - 18:30
Seminar Room A

Convener: Professor Alis Oancea, Skills, Knowledge and Organisational Performance (SKOPE) research group

Internet use and health: using secondary data for spatial microsimulation.

Ulrike Deetjen, Oxford Internet Institute

08 June 2015 12:15 - 13:45
Seminar Room E

Conveners: Dr Lars-Erik Malmberg, Quantitative Methods Hub

 

Mathematics Education Reading Group

11 June 2015 15:00 - 16:30
Seminar Room G

Convener: Dr Gabriel Stylianides, Mathematics Education Research Group (MERG)

Reading

Concepts and mastery in learning and teaching mathematics

Dr Alf Coles, University of Bristol

11 June 2015 16:30 - 18:00
Seminar Room G

Convener: Dr Jenni Ingram, Mathematics Education Research Group

Abstract:  In this session, Alf will consider the question of how we come to acquire mastery over mathematical concepts. Two sources of evidence converge to bring into question the orthodoxy that learning mathematics entails a movement from concrete to abstract. The first is recent neuroscience research into the origins of number sense and the previously unacknowledged role of ordinality (see the work of Ian Lyons). The second source comes from reflection on three of the great mathematics educators of the twentieth century, Caleb Gattegno, Vasily Davydov and Bob Davis. All three authors developed mathematics curricula (shown to be highly effective) in which mathematical symbolism arose out of action and relationship, not as a referrent for concrete objects. Alf will work with the group actively on these ideas and the direct implications for the classroom. There will be space for feedback and discussion of issues.

Bayesian model averaging over directed acyclic graphs with implications for the predictive performance of structural equation models

David Kaplan, University of Wisconsin

15 June 2015 12:15 - 13:45
Seminar Room E

Conveners: Dr Lars-Erik Malmberg, Quantitative Methods Hub

Abstract:
This talk considers Bayesian model averaging as a means of improving the predictive performance of Bayesian structural equation models. Structural equation modeling from a Bayesian perspective addresses the problem of parameter uncertainty through the specification of prior distributions on all model parameters. In addition to parameter uncertainty, it is recognized that there is uncertainty in the choice of models themselves insofar as a particular model is chosen based on prior knowledge of the problem at hand. This form of uncertainty is not accounted for in frequentist structural equation modeling and neither has it been directly addressed in Bayesian structural equation modeling. An internally consistent Bayesian framework for structural equation modeling estimation must also account for model uncertainty. The current approach to addressing the problem of model uncertainty lies in the method of Bayesian model averaging. For this talk, we expand the framework of Madigan and his colleagues as well as Pearl by considering a structural equation model as a special case of a directed acyclic graph. We then provide an algorithm that searches the model space for sub-models that satisfy the conditions of Occam’s razor and Occam's window and obtains a weighted average of the sub-models using posterior model probabilities as weights. Our simulation studies indicate that the model-averaged sub-models provided better posterior predictive performance compared to the estimation of the initially specified model as measured by the log-scoring rule. The talk closes with a discussion of the role of prediction in structural equation modelling.

The rediscovery of teaching: in search of a progressive argument

Professor Gert Biesta, University of Luxembourg and Brunel University

15 June 2015 17:00 - 18:30
Seminar Room A

Convener: Dr Rebecca Enyon, Learning and New Technologies Research Group

Introduction to R for the analysis of international assessment data

Instructor: Dr. Daniel Caro

16 June 2015 09:00 - 17:00
IT Room, Manor Road Building, Manor Road, Oxford, OX1 3UQ

The workshop will introduce the R software environment and train participants in how to analyse data from international assessments (PISA, TIMSS, and PIRLS) using R. It will present the basics of the R language and data analysis in R, including how to create and import data, calculate descriptive statistics, perform regression analysis, and conduct analysis by grouping variables. Lectures will introduce international assessments and the challenges associated with the analysis of assessment data (e.g., plausible values, replicate weights).
Hands-on exercises will reproduce main results in international assessment reports with the R package 'instvy'. The last part of the workshop will be dedicated to an assignment. The workshop is aimed at researchers interested in R and international assessments.

Workshop prerequisites: It is assumed that participants will have a background in basic statistical methods up to, and including, regression analysis. Some familiarity with syntax language from other statistical packages (e.g., Stata, SPSS) is desirable.

Note: This workshop is the first day of a four-day workshop on the analysis of international assessment data using R. This first day adopts a frequentist perspective and the second part (days 2-4) the Bayesian paradigm. Participants are encouraged, but not required, to sign up to the second part on Bayesian statistics by Professor David Kaplan.

Course fee:
Oxford University Participant (Students, Staff): No charge
Other Students: £30
External Other: £100
The course fee includes access to training sessions/events, event materials, lunch and refreshments. The fee does not include accommodation or travel.

Registration:
Oxford University participants should register via Weblearn. Browse by Department and select Education.
Other students and external participants please complete the registration form and return by email to lorena.ortega@education.ox.ac.uk.

ESRC Student Bursaries:

ESRC student bursaries are available to postgraduate students from Higher Education Institutions outside Oxford to provide up to £120 per day financial assistance toward the cost of attending the course. Students will also be able to claim reasonable travel costs within the UK to Oxford, plus reasonable accommodation costs up to £100 per night for the duration of the course. Students must pay upfront for the course and then claim costs back after they have attended, providing receipts for all expenses.

Please note: You must be a postgraduate research student at a UK Higher Education Institution to be eligible for bursary funding.

If you would like to apply for an ESRC student bursary please complete the ESRC bursary application form and return it by email to lorena.ortega@education.ox.ac.uk together with your registration form.

Bayesian methods for international assessments

Instructor: Professor David Kaplan

17 June 2015 -
IT Room, Manor Road Building, Manor Road, Oxford, OX1 3UQ

Three day course: Wednesday 17th - Friday 19th June

The orientation of this workshop is to introduce social scientists to the basic elements of Bayesian statistics and to show through discussion and practice, why the Bayesian perspective provides a powerful alternative to the frequentist perspective. We will use data from international assessments to provide workshop participants with opportunities for practice. In addition, we will focus on the use of existing programs in the R software environment.

Course prerequisite: It is assumed that participants will have a background in basic statistical methods up to, and including, regression analysis. Some exposure to growth curve modelling is desirable.

Note: This workshop is the second part (days 2-4) of a four-day workshop on the analysis of international assessment data using R. Participants who require an introduction to R and international assessments should sign up to the first day workshop by Dr. Daniel Caro (listed above).

Participants are expected to attend the full three days of the course.

Course fee:
Oxford University Participant (Students, Staff): No charge
Other Students: £90
External Other: £300
The course fee includes access to training sessions/events, event materials, lunch and refreshments. The fee does not include accommodation or travel.

Registration:
Oxford University participants should register via Weblearn. Browse by Department and select Education.
Other students and external participants please complete the registration form and return by email to lorena.ortega@education.ox.ac.uk.

ESRC Student Bursaries:

ESRC student bursaries are available to postgraduate students from Higher Education Institutions outside Oxford to provide up to £120 per day financial assistance toward the cost of attending the course. Students will also be able to claim reasonable travel costs within the UK to Oxford, plus reasonable accommodation costs up to £100 per night for the duration of the course. Students must pay upfront for the course and then claim costs back after they have attended, providing receipts for all expenses.

Please note: You must be a postgraduate research student at a UK Higher Education Institution to be eligible for bursary funding.

If you would like to apply for an ESRC student bursary please complete the ESRC bursary application form and return it by email to lorena.ortega@education.ox.ac.uk together with your registration form.