Funded PhD Opportunity

Augmented Reality for Digital Education: Integrating Data Engineering and AI Machine Learning in Applications for Enhanced Learning

Subject: Computer Science and Informatics


Summary

Augmented reality (AR) is a three-dimensional (3D) technology that merges the digital and physical worlds in real time. It enhances the user’s sensory perception of the real world with a contextual layer on information [1]. AR applications rests on three pillars, which include the tools, hardware and software and the devises. The tools are used to track information about the real world, the hardware and the software are used to process the information and the devices are used to show the user the digital information integrated in real environment [2, 3]. Very recently, AR has become an important focus of research education. Studies have shown that it has potential pedagogical applications. There is an increasing gap between the rate at which we acquire and store data and to the rate at which we are able to analyse the data to obtain information in order to make useful decision. Data engineering, which encompasses visual analytics, computer imaging and information visualisation seeks to bridge this gap by using more intelligent means in data analysis.  This involves visually representing information, allowing the user to directly interact with data, gain insight into the data and draw conclusions from the data and ultimately make informed and better decisions.

This project shall use visual analytics tools and techniques integrated in AR applications to synthesize information and derive insight from massive, dynamic and diverse data by providing timely, defensible and understandable assessments for enhanced learning. The proposed project will seek to investigate the characteristics of AR in education with focus on science and engineering. Most AR applications offer simulation or exploration activities with features that are based on digital knowledge discovery mechanisms to utilize information via interaction with digital elements. To date only very few have provided students with help in carrying out learning activities. This project shall assess the effects of AR on students’ conceptual understanding and attainment of affective learning outcomes.

Specifically, the project will investigate and establish

(i) the characteristics and design features of AR-based learning applications for science and engineering education,

(ii) the instructional processes followed by science and engineering AR studies and

(iii) the measured outcomes addressed in AR for science and engineering studies.

The determining and characterising AR applications shall involve investigations and development with AR building tools, various application types, different AR features including their uses involving a variety of learning and instructional strategies. Research points out that AR has potential educational affordances which are especially useful in the science and engineering fields, such as spatial ability, conceptual understanding, practical skills and scientific inquiry learning [5, 6, 7]. The present project shall focus on science and engineering contexts.


Essential criteria

  • Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC)
  • Sound understanding of subject area as evidenced by a comprehensive research proposal

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • Publications record appropriate to career stage
  • A comprehensive and articulate personal statement
  • Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding

    The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

    Vice Chancellors Research Studentship (VCRS)

    Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,000 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.

    Vice-Chancellor’s Research Bursary (VCRB)

    Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £7,500 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.

    Vice-Chancellor’s Research Fees Bursary (VCRFB)

    Fees only award (PhD fees + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.

    Department for the Economy (DFE)

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 15,009 per annum for three years. EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.

    Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies


Other information


The Doctoral College at Ulster University


Reviews

As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day

Adrian Johnston - PhD in Informatics

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Key dates

Submission deadline
Friday 7 February 2020

Interview Date
Late March 2020


Applying

Apply Online  


Campus

Jordanstown campus

Jordanstown campus
The largest of Ulster's campuses


Contact supervisor

Dr James Uhomoibhi


Other supervisors

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