Work with us for 3 years as a Industry PhD student in "Learning Sciences and Digital Technologies"

RESEARCH PROJECT

Enhancing Adaptive Learning with AI Companions: A Machine Learning Approach

 

DEADLINE FOR APPLICATIONS: August 2nd 2024 1:00 pm

PhD Course Description 

Managing institution: University of Modena and Reggio Emilia

Network universities: 34 italian national universities

Host Company: Osel - e-learning Revolution (osel.it)

Our reference Professor: Prof. Agostino Marengo (Linkedin Profile) - University professor and our co-founder

The PhD program in Learning Sciences and Digital Technologies is designed to investigate the relationships between technologies and social and material contexts in educational processes. One of the distinctive features of this program lies in its interdisciplinary nature, incorporating contributions from both hard and human sciences.

The central focus of the training and research activities is the theme of emerging and innovative technologies and their impact on teaching and learning processes for the development of methodological approaches and of original solutions and tools. PhD students will acquire knowledge of the pedagogical and neuroscientific fundamentals of learning, teaching theories, and digital design to develop new technologies, analyze educational big data, and design teaching and assessment methods and tools. The program initiatives will also address legal issues related to data management and privacy protection, the training of individuals with disabilities and special educational needs in formal, informal, or non-formal contexts, educational and rehabilitative strategies for socially vulnerable or disadvantaged groups.

Students will develop specialized knowledge by participating in relevant research projects involving academic and industrial/professional communities.

Our Industry PhD Project

Enhancing Adaptive Learning with AI Companions: A Machine Learning Approach

Main goals:

1. Development of AI Companions: Design and implementation of artificial intelligence "companions" capable of interacting naturally with students, offering personalized support based on individual needs.


2. Integration of Machine Learning: Application of Machine Learning algorithms for the analysis of learning data, student profiling, performance cluster prediction, and prevention of poor practices, as well as the ability to adapt educational content in real-time.


3. Personalization of Learning: Development of methods to personalize educational pathways based on students' abilities, preferences, and progress, improving learning effectiveness.


4. Evaluation of Effectiveness: Assessment of the proposed system's impact on student learning through empirical studies and experiments.

Impact of the Proposed Research

The project will have a significant impact in several areas:

1. Improvement of Environmental Sustainability: The adoption of digital technologies reduces the need for physical teaching materials, contributing to a reduction in resource consumption and CO2 emissions associated with the production and transportation of these materials.


2. Acceleration of Digital Transformation Processes: The project promotes the adoption of advanced technologies in education, facilitating the transition towards a more digital and innovative educational system.


3. Promotion of Social Inclusion: AI Companions can be used to support students with diverse abilities and from various socio-economic backgrounds, offering personalized and inclusive learning.

Operational and Scientific Structures

The project will be developed at OSEL SRL, including remote work. The company has resources for artificial intelligence and machine learning and highly qualified personnel and adequate infrastructure to ensure the project's success.

Duration: three years
Starting: Nov, 1st 2024

Application deadline: August 2nd, 2024
Available positions: 1

Training and Research Activities

The successful PhD candidate will be involved in a training program that includes:

- 24-30 months of activities at the company: Collaboration on practical projects to apply theoretical knowledge in real-world contexts.
- 6-12 months of research abroad: Collaborations with internationally renowned academic institutions to broaden perspectives and acquire new skills.

During the doctoral program, the candidate will participate in workshops, seminars, and conferences, contributing to the dissemination of research results and the growth of their professional network. This approach will ensure comprehensive training, balanced between theory and practice, enriched by international experiences.

ADMISSION REQUIREMENTS

Applicants must be in possession of either an Italian higher level degree (laurea specialistica under D.M. 509/99 or laurea magistrale under D.M. 270/04), or an Italian degree obtained prior to D.M. 509/99, or an equivalent qualification obtained abroad.
More information available in the call for admission.

At a glance

Submission Deadline: August 2nd, 2024 - 13.00 CET
Admission to interview notification: August 19th-23rd, 2024
Interviews: from August 26th, 2024 - 9.00 AM CET (online)
Program starting: November 1st, 2024
Official Notice Board from UNIMORE/OSEL: English | Italiano
Evaluation phases and scores:
- Titles score: up to a maximum of 20 points;
- Research project score: up to a maximum of 40 points, with a minimum score for admission to the oral test of 27/40;
- Oral test score: up to a maximum of 60 points (including the English language proficiency test), with a minimum score of 41/60.
The maximum score achievable, given by the sum of the points from the above-mentioned tests, is therefore 120 points.
At the end of the examination tests, the selection board will draw up an overall ranking list on the basis of the scores obtained by the candidates.

Submission Process for Doctoral Application

Key Steps and Requirements: contact us, we will provide any assistance for the submission

 

==> Ask for documents and submission procedure <==

Prof. Agostino Marengo [email protected]

 

Deadline for Application Submission:

- Date: Applications must be submitted by 2 August 2024, 1:00 PM.
- Procedure: The submission must be done through the specified online procedure.

Online Application Process:

- Registration: Candidates must register on the university’s portal
- Login: After registration, candidates need to log in using their credentials or SPID (Public Digital Identity System).
Required Documents and Attachments:

All documents must be in electronic format (.pdf or .rtf) and should not exceed 20 MB. Larger documents must be divided into parts.
Necessary documents include academic titles, publications, and any other relevant documents for the selection process.

Application Fee:

- Amount: €25.00, non-refundable.
- Payment Method: Payment must be made through the PagoPA system, accessible via the Esse3 portal under the "Tasse" menu.

Formalities for Submission:

- Saving Data: The application is considered submitted only after saving the data following the explicit confirmation of the validity of the application.
- Modifications: Candidates can modify or add documents before the final submission deadline by logging back into the system.
Special Cases:

Errors in Submission: If there are errors or incomplete attachments, candidates can request the reopening of the procedure by emailing [email protected] before the deadline, providing identification documents and necessary corrections.
Non-acceptance: Applications submitted via email or fax will not be accepted.
Required Declarations:

Personal Information: Candidates must declare their name, date of birth, residence, contact details, and nationality.
Academic Qualifications: Information about secondary school qualifications and higher education degrees.
Research Project and Preferences: Submission of the research project and preferences for the assignment (up to 5 choices).
CV and Additional Documents: Curriculum vitae and other relevant documents and publications.

Submission Confirmation:

After completing the application, a summary memo of the application is generated, which should be kept by the candidate.


==> Ask for documents and submission procedure <==

Prof. Agostino Marengo [email protected]