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

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

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• 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 and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

• Full Award: (full-time tuition fees + £19,000 (tbc))
• Part Award: (full-time tuition fees + £9,500)
• Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) 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 support grant (RTSG) allocation to help support the PhD researcher.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living