INFORMATION TECHNOLOGY APPLIED TO THE PROFESSION
- Overview
- Assessment methods
- Learning objectives
- Contents
- Full programme
- Teaching methods
- Contacts/Info
None
ADMISSION RULES:
No distinction is made between attending and non-attending students. There are no preparatory activities or other tasks required to access the exam.
TYPE OF EXAM:
The exam is written, aims to assess the knowledge acquired on the topics covered during the course, and is delivered through a web platform.
EXAM PROCEDURES:
The classroom is typically traditional (not computer-equipped). Students must bring their own device (computer or tablet) with an internet connection to take the exam. Students may only use the exam website.
ASSESSMENT CRITERIA:
The exam is graded on a 30-point scale.
A multiple-choice questionnaire is administered through a dedicated platform.
It is a timed exam lasting 38 minutes.
Students receive written confirmation of their participation via email from the instructor, with specific instructions regarding the exam.
The questionnaire—accessible via a link (the same for everyone) sent by email—and the access password provided at the time of the exam includes multiple-choice questions and 2 open-ended questions, for a total of 30 questions.
1 point is awarded for each correct answer.
The questions (and their order) are distributed automatically by the system.
The instructor does not know the questions in advance.
The environment is a web platform, and navigation follows its standard structure.
At the bottom of the page, the “submit” button sends the responses.
The results of the multiple-choice section are immediately available.
If the time expires, the exam is still submitted and evaluated by the system.
The instructor can verify in real time that the exam has been submitted, but not the responses.
Only once the system is unlocked can the instructor access and download the data for evaluation.
In this phase, it is also possible to send a report with the results of the questions, which are already visible to the student.
Once the results have been reviewed, the platform may be closed and the session ended.
The questionnaire format, in its structure and timing, is considered appropriate for evaluating the learning objectives of this course. Multiple-choice questions assess specific, factual knowledge.
1. LEARNING OUTCOMES (DUBLIN DESCRIPTORS)
1. Knowledge and Understanding
At the end of the course, the student will have acquired:
Fundamental principles of computer science and the safe and effective use of digital systems in healthcare.
Knowledge of cybersecurity risks, personal data protection (GDPR), digital preservation, and patient privacy.
Foundations of online collaboration: secure document sharing, management of collaborative platforms, and digital communication in healthcare.
Basics of artificial intelligence, big data, and the use of scientific healthcare databases (PubMed, Cochrane, guidelines).
Essential computer tools for clinical practice and study: file management, cloud services, email, and office automation.
2. Applying Knowledge and Understanding
At the end of the course, the student will be able to:
Appropriately use computers, operating systems, browsers, and web tools for academic and clinical purposes.
Apply good cybersecurity practices (passwords, authentication, backup, encryption, protection of sensitive data).
Use digital platforms for collaboration and the sharing of clinical data in compliance with regulations.
Access, evaluate, and use scientific databases to support evidence-based clinical decision-making.
Use basic AI tools in a critical and responsible way (support for literature searches, document summarization, data analysis).
3. Making Judgements
The student will be able to:
Identify digital risks and vulnerabilities in clinical settings.
Evaluate the reliability of online scientific sources and the information systems used in healthcare.
Select appropriate digital tools according to purpose, considering ethical, privacy, and security aspects.
Recognize opportunities and limitations of AI in healthcare and dentistry.
4. Communication Skills
The student will be able to:
Communicate clinical information through digital tools clearly, securely, and professionally.
Interact effectively on collaborative academic or clinical platforms.
Use basic technical-informatic terminology to describe problems, solutions, and digital processes.
5. Learning Skills
At the end of the course, the student will have developed:
Skills to independently update their knowledge on new digital tools and emerging technologies in dentistry.
Methods for autonomous research of resources, tutorials, and technical documentation.
The ability to use computer tools to enhance studying, information management, and clinical practice.
Module 1 — Computer Essentials
Hardware, software, operating systems
File and folder management, cloud storage, backup
Productivity tools (word processing, spreadsheets, presentations)
Basic computer configuration in a clinical environment
Module 2 — Online Essentials
Web browsing, search engines, and scientific search strategies
Digital identity, email management
Secure access to online services
Assessing the reliability of online healthcare information
Module 3 — IT Security
Cybersecurity risks in healthcare (malware, phishing, ransomware)
Authentication: passwords, MFA, secure credential management
Data protection and patient privacy (GDPR and healthcare context)
Device and network security
Concepts of encryption, digital preservation, and healthcare document management
Module 4 — Online Collaboration
Collaborative tools: file sharing, calendars, videoconferencing
Digital etiquette in professional communication
LMS platforms and the electronic portfolio for dentistry students
Secure management of shared clinical documents
Module 5 — Artificial Intelligence, Big Data and Healthcare Databases
Generative and non-generative AI in medicine and dentistry
Clinical applications: radiological diagnosis support, CDSS, imaging workflows
Big Data in healthcare: information flows, interoperability, digital health
Advanced literature research: PubMed, Cochrane, clinical guidelines
Ethics, limitations, and critical issues of AI in the dental field
1. COMPUTER ESSENTIALS (approx. 8 hours)
Main contents:
Role of digital technologies in dentistry: electronic health record, imaging, patient communication
Hardware, software, operating systems
Computer structure: CPU, RAM, storage, peripherals
File and folder management: organization, naming, search
File formats (images, documents, DICOM)
Cloud and data synchronization
Backup: strategies, devices, best practices
Software licenses and open-source tools in healthcare
Productivity applications:
– word processors (clinical reports, forms)
– spreadsheets (management of small clinical datasets)
– presentations (scientific communication)
Expected skills: autonomy in managing one's own digital study and pre-clinical environment.
2. ONLINE ESSENTIALS (approx. 6 hours)
Main contents:
Browser, cookies, cache, extensions
Safe and responsible browsing
Internet search strategies and source evaluation
Criteria for distinguishing reliable information from non-scientific sources
Professional email: mailbox management, certified email (PEC), digital signature
Healthcare attachments (images, PDFs, reports) and their secure handling
Communication risks: phishing, spam, social engineering
Digital identity of the student and future healthcare professional
Expected skills: ability to find, evaluate and use online information with critical judgment.
3. IT SECURITY (approx. 14 hours)
Main contents:
Basic security (shared section)
Fundamentals of cybersecurity: threats, attacks, vulnerabilities
Malware: viruses, trojans, ransomware
Physical security of devices
Secure passwords, MFA, credential management
Backup, recovery, encryption
GDPR: general principles, health data, responsibilities
Patient privacy: secure transmission of images, documents and reports
Advanced security (non-shared, in-depth section)
Security in a dental practice: risks, procedures, protocols
Network security: firewalls, VPN, segmentation
Wi-Fi security: proper configuration and risks
Security of digital medical devices and healthcare apps
Standards and best practices for compliant storage of clinical documents
Protection of digital diagnostic images (DICOM, encryption, storage)
Expected skills: ability to identify, prevent and manage cybersecurity risks in healthcare.
4. ONLINE COLLABORATION (approx. 6 hours – Dentistry only)
Main contents:
Collaborative platforms: Teams, Google Workspace, Moodle
Secure document sharing: permissions, versioning, encryption
Management of shared calendars, meetings, videoconferencing
Creation of digital workflows (clinical workflows)
Professional netiquette in online communication
Discussion of clinical cases using digital and multimedia materials
Tools for shared annotation of radiological images
Expected skills: ability to work in a digital team and to professionally manage clinical and educational documents.
5. ARTIFICIAL INTELLIGENCE IN DENTISTRY (approx. 6 hours)
Main contents:
What AI is: symbolic models, ML, neural networks
Generative AI: applications useful for students and clinicians (summaries, text analysis, preliminary diagnostic support)
AI and dental imaging:
– analysis of panoramic X-rays, bite-wings, cone-beam CT
– recognition of lesions, caries, structural anomalies
Clinical Decision Support Systems (CDSS)
Ethics and safety of AI: transparency, bias, clinical risk
Examples of AI tools available in the dental field
Expected skills: critical and responsible use of AI as clinical and study support.
6. BIG DATA AND HEALTHCARE DATABASES (approx. 6 hours)
Main contents:
Definition and role of Big Data in medicine and dentistry
Interoperability of healthcare systems: HL7, FHIR, DICOM
Information flows and the electronic health record
Advanced literature search: PubMed, Cochrane, guidelines
Healthcare open data and their use in research
Data quality, standardization, reliability
Expected skills: ability to retrieve and use clinical and scientific data in an advanced way.
Didactic teaching: 32 hours
Lectures (for the theoretical component);
Interactive teaching: 4 hours
Practical exercises (to enhance the ability to relate different types of knowledge and models);
Case study analysis (to improve the ability to apply knowledge and models in analyzing the challenges and opportunities posed by digital technologies in the context of complex organizations).
Remote teaching activities may be provided in the event of specific contingencies.
Office hours:
contact via email at sergio.moriani@uninsubria.it
.
Videoconference if needed.