This is the presentation of my mini viva talk given to examiners who assess my PhD's 1st year following the probationary report. It is a summary of my research aims, what I have been doing since the beginning of my 1st year and my plans for the following years of the PhD
Thesis defense presentation of Justin Phillips (SDSU). "The Role of Relatedness and Autonomy in Motivation of Youth Physical Activity: A Self-Determination Perspective."
Thesis defense presentation of Justin Phillips (SDSU). "The Role of Relatedness and Autonomy in Motivation of Youth Physical Activity: A Self-Determination Perspective."
Thesis PROPOSAL Defense Presentation - March 26 Hermes Huang
This is the Thesis Proposal Defense Presentation by Hermes Huang titled
Analyzing Impacts of Networks within the Maker Movement: The Case of DIYBio in Yogyakarta, Indonesia
A Guide to Write a Research Proposal for Masters DissertationDissertation - T...Tutors India
The research proposal purposes are numerous and all of them are crucial for writing an excellent project for the Master’s Dissertation. If all the expectations of the proposal are fulfilled, Master’s Dissertation Writing will be facile and feasible. The present article helps the USA, the UK, Europe and the Australian students pursuing their master’s degree to identify best research proposal writing help which is usually considered to be difficult. Tutors India offers UK dissertation in various Domains.
When you Order Research Proposal Writing Services at Tutors India, we promise you the following
Plagiarism free
Always on Time
Outstanding customer support
Written to Standard
Unlimited Revisions support
High-quality Subject Matter Experts
Contact:
Website: www.tutorsindia.com
Email: info@tutorsindia.com
United Kingdom: +44-1143520021
India: +91-4448137070
Whatsapp Number: +91-8754446690
Reference: http://bit.ly/2vzHUi0
Thesis PROPOSAL Defense Presentation - March 26 Hermes Huang
This is the Thesis Proposal Defense Presentation by Hermes Huang titled
Analyzing Impacts of Networks within the Maker Movement: The Case of DIYBio in Yogyakarta, Indonesia
A Guide to Write a Research Proposal for Masters DissertationDissertation - T...Tutors India
The research proposal purposes are numerous and all of them are crucial for writing an excellent project for the Master’s Dissertation. If all the expectations of the proposal are fulfilled, Master’s Dissertation Writing will be facile and feasible. The present article helps the USA, the UK, Europe and the Australian students pursuing their master’s degree to identify best research proposal writing help which is usually considered to be difficult. Tutors India offers UK dissertation in various Domains.
When you Order Research Proposal Writing Services at Tutors India, we promise you the following
Plagiarism free
Always on Time
Outstanding customer support
Written to Standard
Unlimited Revisions support
High-quality Subject Matter Experts
Contact:
Website: www.tutorsindia.com
Email: info@tutorsindia.com
United Kingdom: +44-1143520021
India: +91-4448137070
Whatsapp Number: +91-8754446690
Reference: http://bit.ly/2vzHUi0
Course Pathways: Making the right choices for the right reasonsSimon Buckingham Shum
Update on the UTS project to analyse student pathways using data mining techniques:
https://utscic.edu.au/projects/uts-projects/course-pathways-analytics
Klink-2: integrating multiple web sources to generate semantic topic networksFrancesco Osborne
ISWC 2015 research paper: http://oro.open.ac.uk/43793/1/ISWC2015_CR.pdf
Abstract:
The amount of scholarly data available on the web is steadily increasing, enabling different types of analytics which can provide important insights into the research activity. In order to make sense of and explore this large-scale body of knowledge we need an accurate, comprehensive and up-to-date ontology of research topics. Unfortunately, human crafted classifications do not satisfy these criteria, as they evolve too slowly and tend to be too coarse-grained. Current automated methods for generating ontologies of research areas also present a number of limitations, such as: i) they do not consider the rich amount of indirect statistical and semantic relationships, which can help to understand the relation between two topics – e.g., the fact that two research areas are associated with a similar set of venues or technologies; ii) they do not distinguish between different kinds of hierarchical relationships; and iii) they are not able to handle effectively ambiguous topics characterized by a noisy set of relationships. In this paper we present Klink-2, a novel approach which improves on our earlier work on automatic generation of semantic topic networks and addresses the aforementioned limitations by taking advantage of a variety of knowledge sources available on the web. In particular, Klink-2 analyses networks of research entities (including papers, authors, venues, and technologies) to infer three kinds of semantic relationships between topics. It also identifies ambiguous keywords (e.g., “ontology”) and separates them into the appropriate distinct topics – e.g., “ontology/philosophy” vs. “ontology/semantic web”. Our experimental evaluation shows that the ability of Klink-2 to integrate a high number of data sources and to generate topics with accurate contextual meaning yields significant improvements over other algorithms in terms of both precision and recall.
Valedictory Lecture
Making Thinking Visible in Complex Times
Prof Simon Buckingham Shum
This event took place on 15th July 2014 at 4:00pm (15:00 GMT)
Berrill Lecture Theatre, The Open University, Walton Hall Campus, Milton Keynes, United Kingdom
In 1968 Doug Engelbart gave “The Mother of All Demos”: a disruptive technology lab had quietly invented the mouse, collaborative on-screen editing, hyperlinks, video conferencing, and much more. This was the start of the paradigm shift, still unfolding: computers were no longer to be low level number crunchers, but might mediate and mould the highest forms of human thinking, both individual and collective. In this talk I review nearly 19 years in KMi chasing this vision with many colleagues, inventing tools for making dialogue, argument and learning processes visible in different ways. How do we harness such tools to tackle, not aggravate, the fundamental challenge facing the educational system, and its graduates: to think broadly and deeply, and to thrive amidst profound uncertainty and complexity? These are the hallmarks of the OU — and indeed, all true education from primary school onwards.
The ontology engineering research community has focused for many years on supporting the creation, development and evolution of ontologies. Ontology forecasting, which aims at predicting semantic changes in an ontology, represents instead a new challenge. In this paper, we want to give a contribution to this novel endeavour by focusing on the task of forecasting semantic concepts in the research domain. Indeed, ontologies representing scientific disciplines contain only research topics that are already popular enough to be selected by human experts or automatic algorithms. They are thus unfit to support tasks which require the ability of describing and exploring the forefront of research, such as trend detection and horizon scanning. We address this issue by introducing the Semantic Innovation Forecast (SIF) model, which predicts new concepts of an ontology at time t+1 , using only data available at time t. Our approach relies on lexical innovation and adoption information extracted from historical data. We evaluated the SIF model on a very large dataset consisting of over one million scientific papers belonging to the Computer Science domain: the outcomes show that the proposed approach offers a competitive boost in mean average precision-at-ten compared to the baselines when forecasting over 5 years.
The Election Debate Visualisation Project - KMi Internal Seminar - 19 June 2014EDV Project
During the 2010 UK general election, the first ever televised Prime Ministerial debates took place. Research and pilot work in KMi and at University of Leeds demonstrated the interest that this sparked in the public, their need for more understanding of the issues, and the potential of mapping the debates in visual ways. In 2015 the next election is anticipated with public debates. The 3 year EPSRC-funded Election Debate Visualisation (EDV) Project [http://edv-project.net] will take this opportunity to investigate new ways in which the public can replay the debates, and engage more deeply with the issue and arguments at stake. In this talk, we will reflect on the current experience of watching debates, summarise key findings from citizen focus groups, show how we have prototyped a new kind of richer audience feedback and video annotation interface (using the televised/streamed Clegg-Farage EU Debates as an example), and indicate where we’re going. Your thoughts on this are most welcome.
This power point pres will be useful for all the budding PhD aspirants who are preparing for their viva irrespective of their subject. Good Luck & All the Best !
Doing better things: transforming how we use Turnitin for learningJisc
Students have an increasing expectation for academic interactions via the same all-pervasive technologies they use socially. How to marry this need for digital engagement with the rigours and expectations of the assessment process is a challenge faced by many institutions.
Beyond being a mechanism for managing academic misconduct Turnitin, via Feedback Studio is increasingly being adopted by institutions as a tool for Electronic Management of Assessment (EMA) in order to address this challenge.
Learn how technology is engaging and empowering students in the assessment process through innovative approaches to providing constructive and timely feedback beyond a tick or a cross.
Action-Oriented Research Agenda on Library Contributions to Student Learning ...Lynn Connaway
Connaway, Lynn Silipigni, William Harvey, Vanessa Kitzie, and Stephanie Mikitish. 2017. “Action-Oriented Research Agenda on Library Contributions to Student Learning and Success.” Presented at the ALA Midwinter Meeting, Atlanta, Georgia, January 22.
Action-Oriented Research Agenda on Library Contributions to Student Learning ...OCLC
Connaway, Lynn Silipigni, William Harvey, Vanessa Kitzie, and Stephanie Mikitish. 2017. “Action-Oriented Research Agenda on Library Contributions to Student Learning and Success.” Presented at the ALA Midwinter Meeting, Atlanta, Georgia, January 22.
Communicating Their Stories: Strategies to Help Students Write Powerful Colle...Rebecca Joseph
We believe that all high school English teachers can help students begin to prepare for college by embedding personal narratives into their curricula. Students must write powerful college application and scholarship essays as seniors. What better way to help students write authentic stories by helping them throughout high school learn how to write about themselves?
Are They Being Served? Reference Services Student Experience Project, UCD Lib...UCD Library
Presentation given by Jenny Collery and Dr Marta Bustillo, College Liaison Librarians at University College Dublin Library, at the CONUL Annual Conference held on May 30-31, 2018 in Galway, Ireland.
Literature Review (Review of Related Literature - Research Methodology)Dilip Barad
Literature Review or Review of Related Literature is one of the most vital stages in any research. This presentation attempts to throw some light on the process and important aspects of literature review.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
2. Research Aim
• To investigate
• Whether or not computational techniques can automatically
identify attributes of good scholarly writing
• What is the potential of these techniques for student essay
analysis?
• How we can best feedback the results of such analysis in a way
that learners can value to improve the quality of their writing.
• How educators can use these results for automatic or semi-
automatic assessment of their students writing.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
3. Good Scholarly Writing?
Quality of Writing?
• Signalled by the use of
metadiscourse markers in
the text.
• Metadiscourse:
• Linguistic cues in the text
• Expresses a viewpoint, the problem, claim, argument, the
evidence and the implications
• Engages the readers, and signals the writer's stance.
Italicised words are example metadiscourse markers
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
4. Xerox Incremental Parser (XIP)
• Automatic processing of scientific documents
• Recognition of the rhetorically significant sentences
• 8 categories of Rhetorical Moves
• Background Knowledge
• Summarising
• Tendency
• Novelty
• Significance
• Surprise
• Open Question
• Contrasting Ideas
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
6. Original Contribution of PhD
• Carrying XIP into the education field
• For professional scientific articles written by experienced
researchers
• But now for analysis of student essays
• Hypothesis: An outcome of the XIP processed scientific
documents can demonstrate the quality of the author’s written
discourse; and therefore can be used to scaffold and assess
scholarly writing.
• First in depth opportunity to
• Assess a state of the art language technology
• Integrate its services into software tools for academic writing
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
7. Research Questions
• Main Research Question
• How can we support students’ scholarly writing skills to improve the
quality of their writing through automated metadiscourse analysis?
• Sub-Question 1
• How reliable and sufficient are the automated discourse analysis tools
for finding good attributes of scholarly writing within student essays?
• Sub-Question 2
• To what extent is there a relation between the existences of various
kinds of argumentative discourse moves in student essays with final
grades?
• Sub-Question 3
• To what extent automated metadiscourse analysis of discipline-
independent student essays can be used to provide formative feedback?
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
20. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
21. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
22. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
23. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
24. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
25. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
26. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
27. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
28. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
29. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
30. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
• Computational Linguistics:
Possible automated analysis of
scientific & technical writing but
barely deployed in educational
context!
• Need: XIP output is not
educator/learner friendly.
31. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
• Computational Linguistics:
Possible automated analysis of
scientific & technical writing but
barely deployed in educational
context!
• Need: XIP output is not
educator/learner friendly.
32. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
• Computational Linguistics:
Possible automated analysis of
scientific & technical writing but
barely deployed in educational
context!
• Need: XIP output is not
educator/learner friendly.
33. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
• Computational Linguistics:
Possible automated analysis of
scientific & technical writing but
barely deployed in educational
context!
• Need: XIP output is not
educator/learner friendly.
34. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
• Computational Linguistics:
Possible automated analysis of
scientific & technical writing but
barely deployed in educational
context!
• Need: XIP output is not
educator/learner friendly.
35. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
• Computational Linguistics:
Possible automated analysis of
scientific & technical writing but
barely deployed in educational
context!
• Need: XIP output is not
educator/learner friendly.
36. • Learning Analytics: Promising
potential of automated, timely
& formative feedback.
• Unresolved Question: “What does
analytics look like for a higher
order skill such as communicating
ideas in scientific writing, with a
primary focus on assessing
students?”
Literature Review Journey
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
• Academic Writing: Writers
signal argumentative moves by
using well-established patterns
• Debate on whether these
patterns are discipline
independent or not
• Computational Linguistics:
Possible automated analysis of
scientific & technical writing but
barely deployed in educational
context!
• Need: XIP output is not
educator/learner friendly.
• Run XIP on essays from different
disciplines
• Validate XIP in educational
context
• If we can show there is a value
for learners & educators then it
has a potential for formative
assessment of writing.
37. Pilot Work: XIP Dashboard
• Aim: Visualise XIP output
• Question in mind: Can visual XIP analysis of literature help
users to assess current state of the art in terms of trends,
patterns, gaps, and connections?
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
38. Pilot Work: XIP Dashboard
• Aim: Visualise XIP output
• Question in mind: Can visual XIP analysis of literature help
users to assess current state of the art in terms of trends,
patterns, gaps, and connections?
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
Data Set
Proceedings of the Learning Analytics and
Knowledge (LAK) conferences and a journal
special issue, and the Educational Data
Mining (EDM) conferences and journal.
39. Pilot Work: XIP Dashboard
• Aim: Visualise XIP output
• Question in mind: Can visual XIP analysis of literature help
users to assess current state of the art in terms of trends,
patterns, gaps, and connections?
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
Data Set
Proceedings of the Learning Analytics and
Knowledge (LAK) conferences and a journal
special issue, and the Educational Data
Mining (EDM) conferences and journal.
40. Pilot Work: XIP Dashboard
• Aim: Visualise XIP output
• Question in mind: Can visual XIP analysis of literature help
users to assess current state of the art in terms of trends,
patterns, gaps, and connections?
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
XIP Analysis
All of the papers (66 LAK and 239 EDM
papers 305 in total) were analysed
using XIP, extracting 7847 sentences
and 40163 concepts.
Data Set
Proceedings of the Learning Analytics and
Knowledge (LAK) conferences and a journal
special issue, and the Educational Data
Mining (EDM) conferences and journal.
41. Pilot Work: XIP Dashboard
• Aim: Visualise XIP output
• Question in mind: Can visual XIP analysis of literature help
users to assess current state of the art in terms of trends,
patterns, gaps, and connections?
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
XIP Analysis
All of the papers (66 LAK and 239 EDM
papers 305 in total) were analysed
using XIP, extracting 7847 sentences
and 40163 concepts.
Data Set
Proceedings of the Learning Analytics and
Knowledge (LAK) conferences and a journal
special issue, and the Educational Data
Mining (EDM) conferences and journal.
42. Pilot Work: XIP Dashboard
• Aim: Visualise XIP output
• Question in mind: Can visual XIP analysis of literature help
users to assess current state of the art in terms of trends,
patterns, gaps, and connections?
XIP Output: Not learner friendly
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
XIP Analysis
All of the papers (66 LAK and 239 EDM
papers 305 in total) were analysed
using XIP, extracting 7847 sentences
and 40163 concepts.
Data Set
Proceedings of the Learning Analytics and
Knowledge (LAK) conferences and a journal
special issue, and the Educational Data
Mining (EDM) conferences and journal.
43. Pilot Work: XIP Dashboard
• XIP Dashboard is a set of visual analytics modules built on XIP
output.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
44. Pilot Work: XIP Dashboard
• XIP Dashboard is a set of visual analytics modules built on XIP
output.
Paper Prototype & User Evaluation
6 user sessions were conducted with
1st year PhD students from OU
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
45. Pilot Work: XIP Dashboard
• XIP Dashboard is a set of visual analytics modules built on XIP
output.
Paper Prototype & User Evaluation
6 user sessions were conducted with
1st year PhD students from OU
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
46. Pilot Work: XIP Dashboard
• XIP Dashboard is a set of visual analytics modules built on XIP
output.
Paper Prototype & User Evaluation
6 user sessions were conducted with
1st year PhD students from OU
XIP Dashboard
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
47. Dissemination of Work
• Various poster presentations & talks.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
48. Dissemination of Work
• Various poster presentations & talks.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
49. Dissemination of Work
• Various poster presentations & talks.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
50. Dissemination of Work
• Various poster presentations & talks.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
51. Dissemination of Work
• Various poster presentations & talks.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
52. Dissemination of Work
• Various poster presentations & talks.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
53. Dissemination of Work
• Various poster presentations & talks.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
54. Dissemination of Work
• Various poster presentations & talks.
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
55. What are the Next Plans?
• Design refinements to the XIP Dashboard
• User evaluations
• XIP as an API, Web Service
• Integrate to software tools, XIP Dashboard
• Test XIP’s power on student essays
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
56. Data Collection & Analysis
What? When? How? Why?
Student Essays
of OU’s S288
S288-12B (2012
Course)
• Analysis of student essays
through XIP
• Comparison of XIP findings
with final grades
• To see whether XIP can identify
important parts of student
essays
• To see whether or not we can
correlate XIP results with final
grades
Student Essays
of OU’s S288
S288-13B (2013
Course)
Same as two above
• Use of Google Docs for
collaboratively written report
where we back up the
revision history & analyse
through XIP
Same as two above
• To see whether XIP can reveal
interesting predictive patterns
about the quality of the end
document and the final grade.
Student Essays
of OU’s S288
S288-14B (2014
Course)
Same as above
• Develop software with XIP
Visual Analytics Dashboard
integrated
• Get users’ reactions
Same as above
• Analyses student essays &
provide real-time analytics of
students’ essays as a feedback to
students.
Student Essays
(soft domains)
N/A Same as above Same as above
• Test the discipline independency
of XIP
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
57. Data Collection & Analysis
What? When? How? Why?
Student Essays
of OU’s S288
S288-12B (2012
Course)
• Analysis of student essays
through XIP
• Comparison of XIP findings
with final grades
• To see whether XIP can identify
important parts of student
essays
• To see whether or not we can
correlate XIP results with final
grades
Student Essays
of OU’s S288
S288-13B (2013
Course)
Same as two above
• Use of Google Docs for
collaboratively written report
where we back up the
revision history & analyse
through XIP
Same as two above
• To see whether XIP can reveal
interesting predictive patterns
about the quality of the end
document and the final grade.
Student Essays
of OU’s S288
S288-14B (2014
Course)
Same as above
• Develop software with XIP
Visual Analytics Dashboard
integrated
• Get users’ reactions
Same as above
• Analyses student essays &
provide real-time analytics of
students’ essays as a feedback to
students.
Student Essays
(soft domains)
N/A Same as above Same as above
• Test the discipline independency
of XIP
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
RQ1: How reliable and
sufficient are the automated
discourse analysis tools for
finding good attributes of
scholarly writing within
student essays?
58. Data Collection & Analysis
What? When? How? Why?
Student Essays
of OU’s S288
S288-12B (2012
Course)
• Analysis of student essays
through XIP
• Comparison of XIP findings
with final grades
• To see whether XIP can identify
important parts of student
essays
• To see whether or not we can
correlate XIP results with final
grades
Student Essays
of OU’s S288
S288-13B (2013
Course)
Same as two above
• Use of Google Docs for
collaboratively written report
where we back up the
revision history & analyse
through XIP
Same as two above
• To see whether XIP can reveal
interesting predictive patterns
about the quality of the end
document and the final grade.
Student Essays
of OU’s S288
S288-14B (2014
Course)
Same as above
• Develop software with XIP
Visual Analytics Dashboard
integrated
• Get users’ reactions
Same as above
• Analyses student essays &
provide real-time analytics of
students’ essays as a feedback to
students.
Student Essays
(soft domains)
N/A Same as above Same as above
• Test the discipline independency
of XIP
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
RQ1: How reliable and
sufficient are the automated
discourse analysis tools for
finding good attributes of
scholarly writing within
student essays?
RQ2: To what extent is there
a relation between the
existences of various kinds
of argumentative discourse
moves in student essays
with final grades?
59. Data Collection & Analysis
What? When? How? Why?
Student Essays
of OU’s S288
S288-12B (2012
Course)
• Analysis of student essays
through XIP
• Comparison of XIP findings
with final grades
• To see whether XIP can identify
important parts of student
essays
• To see whether or not we can
correlate XIP results with final
grades
Student Essays
of OU’s S288
S288-13B (2013
Course)
Same as two above
• Use of Google Docs for
collaboratively written report
where we back up the
revision history & analyse
through XIP
Same as two above
• To see whether XIP can reveal
interesting predictive patterns
about the quality of the end
document and the final grade.
Student Essays
of OU’s S288
S288-14B (2014
Course)
Same as above
• Develop software with XIP
Visual Analytics Dashboard
integrated
• Get users’ reactions
Same as above
• Analyses student essays &
provide real-time analytics of
students’ essays as a feedback to
students.
Student Essays
(soft domains)
N/A Same as above Same as above
• Test the discipline independency
of XIP
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
RQ1: How reliable and
sufficient are the automated
discourse analysis tools for
finding good attributes of
scholarly writing within
student essays?
RQ2: To what extent is there
a relation between the
existences of various kinds
of argumentative discourse
moves in student essays
with final grades?
RQ3: To what extent
automated metadiscourse
analysis of discipline-
independent student
essays can be used to
provide formative
feedback?
60. Data Collection & Analysis
What? When? How? Why?
Student Essays
of OU’s S288
S288-12B (2012
Course)
• Analysis of student essays
through XIP
• Comparison of XIP findings
with final grades
• To see whether XIP can identify
important parts of student
essays
• To see whether or not we can
correlate XIP results with final
grades
Student Essays
of OU’s S288
S288-13B (2013
Course)
Same as two above
• Use of Google Docs for
collaboratively written report
where we back up the
revision history & analyse
through XIP
Same as two above
• To see whether XIP can reveal
interesting predictive patterns
about the quality of the end
document and the final grade.
Student Essays
of OU’s S288
S288-14B (2014
Course)
Same as above
• Develop software with XIP
Visual Analytics Dashboard
integrated
• Get users’ reactions
Same as above
• Analyses student essays &
provide real-time analytics of
students’ essays as a feedback to
students.
Student Essays
(soft domains)
N/A Same as above Same as above
• Test the discipline independency
of XIP
10/09/2013,Tuesday,TheOpen
University
MiniVivaPresentation
RQ1: How reliable and
sufficient are the automated
discourse analysis tools for
finding good attributes of
scholarly writing within
student essays?
RQ2: To what extent is there
a relation between the
existences of various kinds
of argumentative discourse
moves in student essays
with final grades?
RQ3: To what extent
automated metadiscourse
analysis of discipline-
independent student
essays can be used to
provide formative
feedback?
How can we support
students’ scholarly
writing skills to
improve the quality
of their writing
through automated
metadiscourse
analysis?