Overview
One sentence introduction:
I am a Lecturer in Educational Data Science, meaning I look back on the past in order to look into the future.
Slightly longer:
Motivated by social problems such as unequal access to education and inequality in health and wellbeing, I am interested in educational programmes that unbar the gate without lowering the bar and, research projects that hold promise to help solve or re-solve the problems through improved data analysis and effective storytelling.
Even longer:
I worked in Durham University as a Research Data Scientist before joining the Graduate School of Education in Exeter. In Durham, I conducted follow-up analyses of increasingly big trial data from educational interventions funded by the Education Endowment Foundation (EEF) in England. All EEF projects are independently evaluated by research teams from universities and research organisations. The data from the interventions are then deposited in a data archive which aims to accumulate research findings and help answer research questions surrounding scientific evidence. As the EEF intends to award as much as £200 million by 2025, the archive may also help us better track longer-term impact of the interventions as results from national tests become available where this is possible.
Qualifications
PhD (Durham)
ALB (Harvard)
MPhil (Cambridge)
MSc (Oxford)
Career
Research Data Scientist, Durham University, 2015 - 2018
Research group links
Research
Research interests
As an educational data scientist with an interest in data science education, I am primarily interested in data science for causal inference, evidence generation, synthesis, and communication. In particular, I am interested in counterfactual prediction, the reproducibility of research findings, and if the results researchers reported are sensitive to analytical choices.
I collaborate with colleagues from multiple disciplines and institutions in order to solve some methodological challenges associated with social and educational interventions, for instance, the unintended consequences of randomisation in educational interventions as a result of pupils being randomly allocated to a treatment arm that might be sub-optimal, if not harmful, to them.
To achieve the above goals, I have been working on predictive and personalised approaches to evidence, particularly, individualised treatment effect in clinical trials or Pupil Advantage Index in randomised controlled trials using both conventional regression methods and machine learning techniques.
Understanding that what we observe right in front of our eyes is often ethnographically invisible, I employ mixed methods in my research and draw inspirations from medical anthropology.
Prospective PhD candidates interested in any of the following topics are welcome to get in touch:
- Causal Inference
- Data Science Education
- Digital Education
- Educational Data Science
- Evidence-Informed Policy
- Individualised Treatment Effect
- Mixed Methods Research
- Randomised Controlled Trials (RCT)
Research grants
- 2019 Exeter University
SSIS strategic discretionary research fund to estimate individualised treatment effect for randomised controlled trials using conventional regression models and machine learning algorithms. (£3,500)
- 2019 Exeter University
With Katherin Barg and Lauren Stentiford: A scoping project to automatically extract data from recorded lectures at the University of Exeter. (£2,660)
- 2019 HEFCE
Data Science Education. (£30,000)
- 2019 Exeter University
Data and Science with R. (£2,000)
- 2019 Exeter University
With Alexandra Allan, Karen Knapp, Susan McAnulla, and Matthew Newcombe: Education Incubator Project on flexible blended learning for mature students in the Graduate School of Education and Exeter Medical School. (£9,638)
- 2019 National Institute for Health Research
With Obioha Ukoumunne and Michael Nunns from the Medical School: Cluster randomised trials and child psychiatric epidemiology studentship for three years at UK/EU level. (£58,227)
Links
Publications
Key publications | Publications by category | Publications by year
Key publications
Xiao Z (2019). "You are too out!": a mixed methods study of the ways in which digital divides articulate status and power in China.
Information DevelopmentAbstract:
"You are too out!": a mixed methods study of the ways in which digital divides articulate status and power in China.
This study investigates the differences in adolescent engagement with Information and Communication Technologies (ICT), such as computers, the Internet, and mobile phones. Involving 698 second-year high school students from urban, rural, and ethnic Tibetan regions of China, it finds that patterns of access and use indicate status and power, and the meanings teenagers pour into the technologies articulate social and educational differences. On average, Tibetans are disadvantaged in access, and the return on parental education is greater for the mainstream Han than it is for Tibetans. However, state ‘preferential policies’ have mitigated Tibetans’ plight in use, which makes the least privileged Han students with parents having no more than six years of education.
Abstract.
Full text.
Xiao Z (2019). Mobile phones as life and thought companions.
Research Papers in EducationAbstract:
Mobile phones as life and thought companions
According to adults who ban adolescent interactions with mobile phones in Chinese high schools, students ‘addicted’ to mobile phones lack will power and schools without a restrictive policy on mobile phone use among students on campus are ‘poor’ in quality. Upon analysis of data from 45 semi-structured interviews with second year high school students from urban, rural, and Tibetan regions of China, this study finds that the consequences of mobile phone use are not always pre-determined. Teens do not merely use their phones to connect; they also treat them as ‘life’ and ‘thought’ companions, which they invest with feelings and thoughts that animate life experiences and catalyse healthy development. The wholesale ban on mobile phone use in school is destined to fail and risks blinding parents and educators to potential benefits the technology has to offer, for it overlooks the value of mobile phones as objects of ‘passion’ and ‘reason’, ignores the opportunity to engage with teens who make visible online the problems they struggle with offline, and disregards the need for empathic imagination.
Abstract.
Full text.
Xiao Z (2019). Of young people and Internet cafés.
Abstract:
Of young people and Internet cafés
This study examines how adolescent exposure to Internet cafés (known as wangba in Chinese) relates to academic attainment in urban, rural, and Tibetan schools of China. By documenting the frustrations teenagers express in their negotiations with adults surrounding access to and use of wangba and, by comparing self-reported academic ranking of students from similar backgrounds with how they differ in level of exposure to wangba, the study finds that visiting wangba is not strongly correlated with the probability of students reporting either high or underachievement. While students without any exposure to wangba are substantially less likely than those who have to report academic underperformance, the result becomes random after matching when the logit regression is less model-dependent and vulnerable to the problems associated with missing data. Therefore, exposure to wangba alone is not systematically correlated with academic attainment and that much adult anxiety concerning adolescent visit to wangba is unnecessary.
Abstract.
Author URL.
Xiao Z, Higgins S, Kasim A (2018). Impact Visualisation in Educational Interventions.
Abstract:
Impact Visualisation in Educational Interventions
Reporting of research data analysis often resorts to numerical summaries, such as effect size estimates in Randomised Controlled Trials (RCTs). Summary statistics are helpful and important for evidence synthesis and decision making. However, they can be unstable and inconsistent due to diversity in research designs and variability in analytical specifications. They also mask the dynamics of individual responses to a certain intervention by focusing on average treatment effect on the treated, even though the variation in impact may be crucial information for policy makers. To establish stability and consistency of impact estimates and to reveal the dynamics of individual responses in RCTs, we conduct variable selection, harness the power of noise, implement Cumulative Quantile Analysis (CQA), and devise umbrella plots of loss and gain in this study, using real datasets from over 30 educational interventions funded by the Education Endowment Foundation (EEF) in England. For the purpose of comparison, which is essential in data visualisation, all the aforementioned methods are built upon multiple analytical approaches. We show that the importance of an intervention can be ordered through variable selection, and that the power of noise or the bias induced by inappropriate variables, can be utilised to assess the stability of an impact estimate. We also demonstrate that estimates of average treatment effect cannot fully capture the impact of an intervention on sub-groups of participants with varying levels of attainment at baseline, not to mention individual responses to the intervention. Using CQA and umbrella plots, we are able to supplement what common effect size estimates lack in educational interventions. We argue that the impact of an intervention is often more complex than the average treatment effect suggests, and that until a summary is more informative and able to speak directly to the eye, evidence-based policy and practice cannot be fully achieved.
Abstract.
Author URL.
Xiao Z, Villanueva A, Higgins S (2018). The Case Against Perfection in the Mean.
Abstract:
The Case Against Perfection in the Mean
Analyses of social interventions need to produce evidence relevant to specific groups of people. In this study, we estimated intervention effects for Free School Meal (FSM) pupils in English schools, which is a pre-specified subgroup in most educational interventions funded by the Education Endowment Foundation (EEF) in England. Specifically, we first ran a treatment-FSM interaction test to see if the difference-in-effects is statistically significant between FSM and Non-FSM students. We then calculated separate effect sizes within the two subgroups. Finally, we examined the p-values from the interaction tests and compared the overall effect sizes for both FSM and Non-FSM pupils with the two separate subgroup estimates. We found that conventional interaction tests can produce self-contradictory results. To solve the problem, we proposed an individualised approach to effect estimation and applied it to one EEF dataset. We demonstrated that individualised treatment effects not only indicated where an intervention worked and by how much, but they could also be utilised to optimise treatment recommendation.
Abstract.
Author URL.
Xiao Z, Higgins S (2018). The power of noise and the art of prediction.
INTERNATIONAL JOURNAL OF EDUCATIONAL RESEARCH,
87, 36-46.
Author URL.
Publications by category
Journal articles
Xiao Z (2019). "You are too out!": a mixed methods study of the ways in which digital divides articulate status and power in China.
Information DevelopmentAbstract:
"You are too out!": a mixed methods study of the ways in which digital divides articulate status and power in China.
This study investigates the differences in adolescent engagement with Information and Communication Technologies (ICT), such as computers, the Internet, and mobile phones. Involving 698 second-year high school students from urban, rural, and ethnic Tibetan regions of China, it finds that patterns of access and use indicate status and power, and the meanings teenagers pour into the technologies articulate social and educational differences. On average, Tibetans are disadvantaged in access, and the return on parental education is greater for the mainstream Han than it is for Tibetans. However, state ‘preferential policies’ have mitigated Tibetans’ plight in use, which makes the least privileged Han students with parents having no more than six years of education.
Abstract.
Full text.
Xiao Z (2019). Mobile phones as life and thought companions.
Research Papers in EducationAbstract:
Mobile phones as life and thought companions
According to adults who ban adolescent interactions with mobile phones in Chinese high schools, students ‘addicted’ to mobile phones lack will power and schools without a restrictive policy on mobile phone use among students on campus are ‘poor’ in quality. Upon analysis of data from 45 semi-structured interviews with second year high school students from urban, rural, and Tibetan regions of China, this study finds that the consequences of mobile phone use are not always pre-determined. Teens do not merely use their phones to connect; they also treat them as ‘life’ and ‘thought’ companions, which they invest with feelings and thoughts that animate life experiences and catalyse healthy development. The wholesale ban on mobile phone use in school is destined to fail and risks blinding parents and educators to potential benefits the technology has to offer, for it overlooks the value of mobile phones as objects of ‘passion’ and ‘reason’, ignores the opportunity to engage with teens who make visible online the problems they struggle with offline, and disregards the need for empathic imagination.
Abstract.
Full text.
Xiao Z, Higgins S (2018). The power of noise and the art of prediction.
INTERNATIONAL JOURNAL OF EDUCATIONAL RESEARCH,
87, 36-46.
Author URL.
Xiao Z, Higgins S, Kasim A (2017). An Empirical Unraveling of Lord's Paradox.
The Journal of Experimental Education,
87(1), 17-32.
Full text.
Xiao Z, Kasim A, Higgins S (2016). Same difference? Understanding variation in the estimation of effect sizes from educational trials.
INTERNATIONAL JOURNAL OF EDUCATIONAL RESEARCH,
77, 1-14.
Author URL.
Chapters
Xiao Z, Higgins S (2014). When English Meets Chinese in Tibetan Schools: Towards an Understanding of Multilingual Education in Tibet. In Feng A, Adamson B (Eds.)
Trilingualism in Education in China: Models and Challenges, Dordrecht: Springer, 117-140.
Abstract:
When English Meets Chinese in Tibetan Schools: Towards an Understanding of Multilingual Education in Tibet
Abstract.
Reports
Hutton C, Lukes S, Abdulkader MS, Choudhury R, Gulaid A, Sadia S, Xiao Z, Zere A (2015).
Trusting the dice: immigration advice in Tower Hamlets., Toynbee Hall.
Author URL.
Higgins S, Xiao Z, Katsipataki M (2012).
The impact of digital technology on learning: a summary for the Education Endowment Foundation., Education Endowment Foundation.
Author URL.
Publications by year
2019
Xiao Z (2019). "You are too out!": a mixed methods study of the ways in which digital divides articulate status and power in China.
Information DevelopmentAbstract:
"You are too out!": a mixed methods study of the ways in which digital divides articulate status and power in China.
This study investigates the differences in adolescent engagement with Information and Communication Technologies (ICT), such as computers, the Internet, and mobile phones. Involving 698 second-year high school students from urban, rural, and ethnic Tibetan regions of China, it finds that patterns of access and use indicate status and power, and the meanings teenagers pour into the technologies articulate social and educational differences. On average, Tibetans are disadvantaged in access, and the return on parental education is greater for the mainstream Han than it is for Tibetans. However, state ‘preferential policies’ have mitigated Tibetans’ plight in use, which makes the least privileged Han students with parents having no more than six years of education.
Abstract.
Full text.
Xiao Z (2019). Mobile phones as life and thought companions.
Research Papers in EducationAbstract:
Mobile phones as life and thought companions
According to adults who ban adolescent interactions with mobile phones in Chinese high schools, students ‘addicted’ to mobile phones lack will power and schools without a restrictive policy on mobile phone use among students on campus are ‘poor’ in quality. Upon analysis of data from 45 semi-structured interviews with second year high school students from urban, rural, and Tibetan regions of China, this study finds that the consequences of mobile phone use are not always pre-determined. Teens do not merely use their phones to connect; they also treat them as ‘life’ and ‘thought’ companions, which they invest with feelings and thoughts that animate life experiences and catalyse healthy development. The wholesale ban on mobile phone use in school is destined to fail and risks blinding parents and educators to potential benefits the technology has to offer, for it overlooks the value of mobile phones as objects of ‘passion’ and ‘reason’, ignores the opportunity to engage with teens who make visible online the problems they struggle with offline, and disregards the need for empathic imagination.
Abstract.
Full text.
Xiao Z (2019). Of young people and Internet cafés.
Abstract:
Of young people and Internet cafés
This study examines how adolescent exposure to Internet cafés (known as wangba in Chinese) relates to academic attainment in urban, rural, and Tibetan schools of China. By documenting the frustrations teenagers express in their negotiations with adults surrounding access to and use of wangba and, by comparing self-reported academic ranking of students from similar backgrounds with how they differ in level of exposure to wangba, the study finds that visiting wangba is not strongly correlated with the probability of students reporting either high or underachievement. While students without any exposure to wangba are substantially less likely than those who have to report academic underperformance, the result becomes random after matching when the logit regression is less model-dependent and vulnerable to the problems associated with missing data. Therefore, exposure to wangba alone is not systematically correlated with academic attainment and that much adult anxiety concerning adolescent visit to wangba is unnecessary.
Abstract.
Author URL.
2018
Xiao Z, Higgins S, Kasim A (2018). Impact Visualisation in Educational Interventions.
Abstract:
Impact Visualisation in Educational Interventions
Reporting of research data analysis often resorts to numerical summaries, such as effect size estimates in Randomised Controlled Trials (RCTs). Summary statistics are helpful and important for evidence synthesis and decision making. However, they can be unstable and inconsistent due to diversity in research designs and variability in analytical specifications. They also mask the dynamics of individual responses to a certain intervention by focusing on average treatment effect on the treated, even though the variation in impact may be crucial information for policy makers. To establish stability and consistency of impact estimates and to reveal the dynamics of individual responses in RCTs, we conduct variable selection, harness the power of noise, implement Cumulative Quantile Analysis (CQA), and devise umbrella plots of loss and gain in this study, using real datasets from over 30 educational interventions funded by the Education Endowment Foundation (EEF) in England. For the purpose of comparison, which is essential in data visualisation, all the aforementioned methods are built upon multiple analytical approaches. We show that the importance of an intervention can be ordered through variable selection, and that the power of noise or the bias induced by inappropriate variables, can be utilised to assess the stability of an impact estimate. We also demonstrate that estimates of average treatment effect cannot fully capture the impact of an intervention on sub-groups of participants with varying levels of attainment at baseline, not to mention individual responses to the intervention. Using CQA and umbrella plots, we are able to supplement what common effect size estimates lack in educational interventions. We argue that the impact of an intervention is often more complex than the average treatment effect suggests, and that until a summary is more informative and able to speak directly to the eye, evidence-based policy and practice cannot be fully achieved.
Abstract.
Author URL.
Xiao Z, Villanueva A, Higgins S (2018). The Case Against Perfection in the Mean.
Abstract:
The Case Against Perfection in the Mean
Analyses of social interventions need to produce evidence relevant to specific groups of people. In this study, we estimated intervention effects for Free School Meal (FSM) pupils in English schools, which is a pre-specified subgroup in most educational interventions funded by the Education Endowment Foundation (EEF) in England. Specifically, we first ran a treatment-FSM interaction test to see if the difference-in-effects is statistically significant between FSM and Non-FSM students. We then calculated separate effect sizes within the two subgroups. Finally, we examined the p-values from the interaction tests and compared the overall effect sizes for both FSM and Non-FSM pupils with the two separate subgroup estimates. We found that conventional interaction tests can produce self-contradictory results. To solve the problem, we proposed an individualised approach to effect estimation and applied it to one EEF dataset. We demonstrated that individualised treatment effects not only indicated where an intervention worked and by how much, but they could also be utilised to optimise treatment recommendation.
Abstract.
Author URL.
Xiao Z, Higgins S (2018). The power of noise and the art of prediction.
INTERNATIONAL JOURNAL OF EDUCATIONAL RESEARCH,
87, 36-46.
Author URL.
2017
Xiao Z, Higgins S, Kasim A (2017). An Empirical Unraveling of Lord's Paradox.
The Journal of Experimental Education,
87(1), 17-32.
Full text.
Adetayo K, Xiao Z, Higgins S, De Troyer E (2017). eefAnalytics: Analysing Education Trials.
Author URL.
2016
Xiao Z, Kasim A, Higgins S (2016). Same difference? Understanding variation in the estimation of effect sizes from educational trials.
INTERNATIONAL JOURNAL OF EDUCATIONAL RESEARCH,
77, 1-14.
Author URL.
2015
Hutton C, Lukes S, Abdulkader MS, Choudhury R, Gulaid A, Sadia S, Xiao Z, Zere A (2015).
Trusting the dice: immigration advice in Tower Hamlets., Toynbee Hall.
Author URL.
2014
Xiao Z, Higgins S (2014). When English Meets Chinese in Tibetan Schools: Towards an Understanding of Multilingual Education in Tibet. In Feng A, Adamson B (Eds.)
Trilingualism in Education in China: Models and Challenges, Dordrecht: Springer, 117-140.
Abstract:
When English Meets Chinese in Tibetan Schools: Towards an Understanding of Multilingual Education in Tibet
Abstract.
2012
Higgins S, Xiao Z, Katsipataki M (2012).
The impact of digital technology on learning: a summary for the Education Endowment Foundation., Education Endowment Foundation.
Author URL.
zhimin_xiao Details from cache as at 2019-10-23 11:38:49
Refresh publications
Teaching
I contribute to teaching and supervision of the following modules:
2018 - 2019:
(EFPM308) Preparing for Educational Research and Dissertation.
(ERPM005) Designing and Communicating Research.
(SSI2001) Learning from Work Experience (Undergraduate).
(EFPM329a) Preparing for TESOL Enquiry and Dissertation.
(ERPM100) MSc Programme.
Data and Science with R.
2019 - 2020:
(EFPM005Z1 Class A) Preparing for Educational Enquiry.
(EFPM308) Preparing for Educational Research and Dissertation.
(SSI1001, SSI2001, SSI3017) Learning from Work Experience in Social Sciences (Undergraduate).
Supervision / Group
Postgraduate researchers
- Abdallah Alharbi
- Thana Aljumaah
- Dio Li
- Vichithranie Madurasinghe (College of Medicine and Health)
- Angela Short
- Julio Cesar Torres Rocha
- Yiwen Wang
