Assessment in Digital Learning

Goal and Learning Outcomes

The course seeks to both conceptualize and redefine the purpose and objectives of the 21st century assessment for learning, as well as to outline modern and easy-to-use techniques and tools used by teachers in modern formal and informal learning environments.

After the successful completion of the course, the students will be able to:

  • State the modern forms of educational evaluation, utilizing educational technologies
  • Understand methodological issues regarding the organization and conduct of quality assessment of the educational process.
  • Utilize modern tools and techniques to evaluate trainees’ performance.
  • Apply a variety of techniques for systematic evaluation of instructional process.

 

Contents

  1. Basic principles of evaluating the quality of educational interventions
  • Formative
  • Holistic-Summative
  1. Principles of Monitoring and Assessing Students’ Performance
  2. Known techniques for evaluating the performance of trainees
  3. Categories of assessment tools
  • Quiz-tests
  • Rubrics
  • Mindmaps
  • Learning Analytics
  • Computational Thinking Assessment tools
  1. Quality Evaluation Techniques for Learning Resources and Learning Systems
  2. Process of creation and application of evaluation techniques and tools.

Suggested Reading

  1. A. Tomlinson & T. R. Moon (2013). Assessment and Student Success in a Differentiated Classroom, Association for Supervision & Curriculum Development, ISBN 1416616179 (ISBN13: 9781416616177)
  2. Cowie, B., Moreland, J. and Otrel-Cass, K. (2013). Expanding Notions of Assessment for Learning. Dordrecht: Springer.

Compilers

Learning Outcomes

This course provides an introduction to the principles of analysis and design of programming languages as well as to the ways these principles are applied in modern programming languages. The successful completion of this course will allow students:

  • to understand the basic and important features of the design, implementation and analysis of compiler systems for modern programming languages.
  • to know the basic features of the tools and the development techniques for the creation of modern programming languages.

Course Contents

  • Introduction – Overview of Modern Programming Languages.
  • Language Definition and Design (Regular Expressions – Automata – Context-Free Grammars).
  • Programming Language Structure (Variables, Types and Scoping, Control Flow and Evaluation of Expressions, Subroutines, Iterative and Recursive Processes, Memory Management and Communication).
  • The Compiling/Interpretation Process (Lectical Analysis, Syntactic Analysis, Code Production & Optimization, Linking).

Recommended Readings

  • Scott, M. L., Programming Language Pragmatics, 2nd edition, Morgan Kaufmann, 2009
  • Instructor Notes

Digital Image Processing

Learning Outcomes

Digital image processing is used for two distinct purposes: (1) improving the appearance of the image so that it is easier for an observer to interpret and (2) digitally analyzing the image for the purpose of describing, identifying and interpreting the content of an image. image. The course will present the basic algorithms and methodologies for both purposes in the field of space and in the field of frequencies.

Students, upon successful completion of the course, will be able to:

A) Understand basic methodologies and basic knowledge of designing and developing image processing systems

B) Know the stages of digital image processing and analysis (optical sensors, image capture, digitization, transformation, coding, compression, transmission, segmentation, recognition)

C) Analyze problems across different application areas and select the right mechanisms for managing and processing digital images

D) Evaluate digital image processing systems and algorithms

Course Contents

  • Introduction to Digital Image Processing
  • 2-D Signals and Systems – Background Information
  • Sampling and Digitization Issues
  • Image Enhancement and Restoration
  • Binary Image Processing – Morphological Operators
  • Image Segmentation – Edge Detection
  • Image Transformations (Fourier, DCT, Hadamard, etc.)
  • Analysis in the frequency domain
  • Digital Image Compression
  • Digital Image Analysis – Computer Vision
  • Texture Analysis – Region of Interests
  • Other areas: eg Watermarking, Information Retrieval, etc.

Recommended Readings

  • Rafael C. Gonzalez & Richard E. Woods Digital Image Processing CRC Press 4th Edition

Digital Communications

Learning Outcomes

The aim of the course is to study digital modulation and demodulation techniques in baseband and bandpass telecommunication systems. It presents the detection theory of transmitted communication signals using the method of matched filtering and correlation. The course also covers the analytical evaluation of the performance of digital modulations in additive white Gaussian noise (AWGN) channels in terms of symbol error and bit error probabilities. Finally, an introduction to OFDM multi-carrier transmission and reception is given.

Upon successful completion of the course the student will be able to:

  • Understand the detection theory of digital transmission for baseband and bandpass communication systems.
  • Understand the modulation techniques of ASK, FSK, M-FSK, PSK, DPSK, M-PSK, M-QAM and OFDM.
  • Obtain analytical expressions for the probability of symbol error of various digital modulations in AWGN channel.
  • Understand the pros and cons of various digital modulations in terms of achievable bit rate, error performance, and spectral efficiency.
  • Understand the need of using OFDM in multipath channels.
  • Make simulation models in Matlab/octave in order to evaluate the symbol and bit error probability performance of digital modulations in AWGN.

Course Contents

  • Baseband transmission methods and probability of error for matched filter detection in AWGN.
  • Binary passband modulations: ASK, FSK, and PSK.
  • M-ary signalling: M-FSK, M-PSK, and M-QAM.
  • Demodulation techniques for digital passband modulations and symbol error performance in AWGN channel.
  • Spectral efficiency of digital modulations.
  • Digital filters for zero intersymol interference at the receiver.
  • Noise figure, composite noise figure and noise temperature, calculation of effective receiver temperature.
  • Link budget analysis.
  • Channel coding, convolutional codes and Viterbi algorithm.
  • OFDM transmission and detection.

Recommended Readings

  • Proakis J. & Salehi M. (2001): Communication Systems Engineering, 2nd Edition, Prentice Hall.
  • Sklar B. & Harris F. (2020): Digital Communications: Fundamentals and Applications (Communications Engineering & Emerging Technology Series from Ted Rappaport), 3rd edition, Pearson.

Artificial Intelligence

Learning Outcomes

Upon successful completion of this course, students should be able to

  • Explain fundamental concepts including agents, problem & state/action/ spaces, problem solving via search as a model of thinking, heuristics, knowledge representation and reasoning using logic.
  • Select algorithms for problem solving based on problems characteristics, and characteristics of problem & state/action spaces.
  • Evaluate usefulness, advantages and limitations of various algorithms and methods towards increasing computational effectiveness of problem solving
  • Modelling problems as constraint satisfaction problems, or as problems in logic.

Course Contents

  • Introduction to artificial intelligence, goals, advances, prospects, limitations, and basic notions regarding agents and problem solving.
  • Blind search algorithms
  • Informed search algorithms and proofs of finding optimal solutions
  • Heuristic functions and their construction and selection
  • Local search using hill climbing, simulated annealing, local beam search, genetic algorithms.
  • Constraint problem solving: depth first, depth first with various forms of backtracking, forward checking, arc consistence, maintaining arc consistency, min conflicts.
  • Knowledge representation and reasoning in logic: Propositional logic, entailment, , resolution, satisfiability, DPLL, local search for satisfiability.

Recommended Readings

  • Stuart Russel and Peter Norvig. Artificial Intelligenc­e: A Μodern Approach, Prentice Hall, 2nd edition (2003). http://aima.cs.berkeley.edu/. Το βιβλίο έχει εκδοθεί στα Ελληνικά από τις εκδόσεις Κλειδάριθμος με τον τίτλο «Τεχνητή Νοημοσύνη: Μια σύγχρονη προσέγγιση».http://aima.uom.gr/.
  • Ι. Βλαχάβα, Π. Κεφαλά, Ν. Βασιλειάδη, Φ. Κόκκορα και Η. Σακελαρίου. Τεχνητή Νοημοσύνη. Εκδοτικός οίκος «Β. Γκιούρδας Εκδοτική – Μονοπρόσωπη ΕΠΕ».http://aibook.csd.auth.gr.

Security Policies and Security Management

Learning Outcomes

Within the framework of the course, students will be able:

  • To understand information and systems security problems for public and private bodies
  • To realise the necessity of information security management system ISMS according to ISO 27001:2022
  • To conduct risk management actions according to ISO 27005:2022, starting with risk assessment process and continue with risk treatment process, using software tools
  • To select suitable technological controls, organizational controls, physical controls and people controls, according to ISO 27002:2022
  • To effectively design ISMS and information security polices
  • To understand the challenges posed by the evolving dynamics of the combination of the cognitive fields of cyber security, privacy protection, and Artificial Intelligence and the way they create social, cultural, political, and financial issues, as well as ethical issues in modern societies
  • To possess state-of-the-art specialized scientific knowledge in the subjects of the course as a basis for original thinking and research activities.

Course Contents

  • Information and systems security terminology and ISO 27000:2018
  • Information Security Management System – ISMS: Basic principles and ISO 27001:2022
  • Controls/safeguards: technological controls, organizational controls, physical controls, and people controls according to ISO 27002:2022
  • Information Security Risk management and ISO 27005:2022: assets, threats, vulnerabilities, controls
  • Risk assessment: risk identification, risk analysis, risk evaluation
  • Risk treatment: risk modification, risk retention, risk avoidance, risk sharing
  • Statement of applicability
  • Software for conducting the risk management process
  • Information security organizational framework: Security policies, policies hierarchy, thematic policies, policies life cycle, responsibilities for the development of security policies

Suggested Bibliography

  • R. Anderson, Security Engineering, J. Wiley & Sons, 3rd edition, 2020
  • D. Gollmann, Computer Security, J. Wiley & Sons, 3rd edition, 2011

Scientific Journals

Broadband Networks

Learning Outcomes

The objective of this course is to provide an introduction to broadband technologies and their applications and familiarize students with broadband networks and relevant protocols.

At the end of this course, students will have acquired advanced/in depth knowledge in the field of Broadband Communications Systems, with particular emphasis on baseband processing physical layer techniques, and Medium Access Control design as well as Broadband Networks design and architectures.

The students will be capable of performing numerical calculations of various broadband network parameters, stochastic modelling of transceivers, signal processing algorithm analysis and design and performance assessment by means of analytical evaluations and simulations.

The students will also be capable of comprehending the design principles of a number of Broadband technologies.

Course Contents

  • Introduction to broadband networks, main concepts: bandwidth, transmission basics, switching, multiplexing, spread spectrum, transmission media.
  • Integrated services networks, access networks, core networks, Integrated services networks: integrated services digital networks (ISDN), broadband integrated services digital networks (B-ISDN).
  • Wireline Access networks/technologies: public switched telephone networks (PSTN), digital subscriber line (DSL), wireless-access (broadcasting, mobile, fixed-wireless access–FWA), fiber to the curb/home (FTTX).
  • Core networks/technologies: Ethernet, ethernet wide area networks, optical technologies, synchronous optical networks (SONET), wave division multiplexing (WDM), passive optical networks (PONs).
  • Wireless wide are broadband technologies:  3G (WCDMA), 4G (LTE, LTE-Advanced), 5G.
  • Wireless Local Area Networks: WiFi- IEEE 802.11
  • Internet of Things network infrastructures

Recommended Readings

  • Behrouz A. Forouzan, “Data Communications and Networking”, Fourth edition, McGraw-Hill, 2007
  • W Stallings, Wireless Communciations and Networks, Pearson, 2004.
  • D. Tse, P. Viswanath, Fundamentals of Wireless Communciations, 2005.
  • T. S. Rappaport, Wireless communications – Principles and practices, Pearson, 2002.
  • Russell Τ. (1997): Telecommunication Protocols (McGraw-Hill Education).
  • Cajetan M. Akujuobi, Matthew N.O. Sadiku (1997): Introduction to Broadband Communication Systems, Chapman & Hall/CRC
  • Andrea Goldsmith, Wireless Communications, Cambridge University Press, 2005.

Introduction to Cloud Computing

Learning Outcomes

The main objective of this course is to introduce concepts related to the analysis, design and implementation of computation and storage clouds. With the completion of the course, the student will be in position:

  • to understand the necessary theoretical background for computing and storage clouds environments.
  • to know the methodologies and technologies for the development of applications that will be deployed and offered through cloud computing environments.
  • to be able to realize cloud infrastructures by using IaaS software, while also developing cloud applications by utilizing PaaS software.

Course Contents

  • Introduction to cloud computing.
  • Objectives, challenges, application domains, advantages.
    • Computational and storage cloud architectures
    • Service level agreements, service lifecycle management
  • Infrastructure deployment, federation and management models.
    • Cloud service model, service provisioning and access models
    • Elasticity and scalability techniques
    • Information, account and billing management
  • Implementation and operation / management of computational clouds.
    • Software as a Service layer
    • Platform as a Service layer
    • Infrastructure as a Service layer
    • Virtualization and resource management
  • Implementation and operation / management of storage clouds.
    • Distributed object storage clouds
    • Data storage and retrieval based on content
    • Computational tasks execution in storage clouds
  • Quality of service approaches.
    • Requirements and parameters classification
    • Monitoring and control mechanisms
    • Quality of service guarantees
  • Laboratory exercises.
    • Google AppEngine
    • OpenStack
    • Apache Hadoop / MapReduce

Moreover, the EVDOXOS system is utilized to provide additional useful information to the students as well as exercises that respond to the corresponding thematic topics / sessions covered by the course.

Recommended Readings

  • Α. Velte, T. Velte, R. Elsenpeter, «Cloud Computing: A practical approach»
  • T. Erl, «Cloud Computing: Concepts, Technology & Architecture»
  • B. Sosinsky, «Cloud Computing Bible»G. Reese, «Cloud Application Architectures: Building Applications and Infrastructure in the Cloud»
  • R. Buyya, J. Broberg, A. M. Goscinski, «Cloud Computing, Principles and Paradigms»

Computer Networks II

Learning Outcomes

The aim of the course “Computer Networks II” is to complement the course “Computer Networks I”, in order for the students to deepen their knowledge in Computer Networks and their functions. In particular, through this course the students will get familiar with the operation of the data link layer, the Medium Access Control (MAC) sub-level and the Logical Link Control (LLC) sub-level.

Upon successful completion of the course, the students will be in position to:

  • select and apply parity bit, CRC and hamming techniques,
  • select and apply information retranslation techniques through the computer network,
  • use the corresponding communication protocols,
  • combine their knowledge in the field routing,
  • use the most appropriate protocol according to the needs of the network, based on correction and retransmission techniques, thus developing a critical way of thinking.

Course Contents

  • Section 1: Introduction to the functionality of the Data Link Layer (DLL), Medium Access Control (MAC) and Logical Link Control (LLC) layers, error control, error detection, error correction, retransmission techniques, error detection techniques.
  • Section 2: Cyclic Redundancy Codes (CRC), error correction techniques.
  • Section 3: Hamming techniques, Forward Error Correction (FEC), retransmission techniques.
  • Section 4: Stop-and-Wait (S&W), Alternating Bit Protocol (ABP), Automatic Repeat Request (ARQ), sliding window techniques, Go Back N (GBN), Soptional Repeat (SRP).
  • Section 5: MAC protocols; Aloha; Carrier Sense Multiple Access (CSMA); MAC protocols in Wireless Section 6: LANs/MANs/PANs; ΙΕΕΕ 802; x standards; LLC protocols; 802.2 standard.
  • In addition, articles, web addresses for useful information, as well as exercises for practicing students are posted in the platform Evdoxos.

Recommended Readings

  • Walrand J. (1997): Communication Networks, Prentice Hall.
  • Russell T. (1997): Telecommunications protocols, McGraw-Hill.

Associated scientific Journals

  • ΙΕΕΕ Computer Networks
  • IEEE Communications Magazine
  • EEE Access
  • IEEE Wireless Communications
  • International Journal of Network Management
  • Transactions on Emerging Telecommunications Technologies
  • EURASIP Journal on Wireless Communications and Networking

Business Process Management

Learning Outcomes

The objective of this course is to present fundamental principles of Business Process Management (BPM) and to study various methods and techniques for analyzing, modeling, automating, executing and optimizing business processes. The course will incorporate a laboratory component with well-known BPM software tools that allow students to practice some of the principles addressed.

Upon successful completion of this course student will be able to:

  • Create business process models by using BPMN based modelling tools
  • Execute business processes by using Business Process Management Systems
  • Analyze the performance of existing business processes and improve business processes that are not sufficient according to certain criteria
  • Create business process management strategies and business processes implementation plans within organizations

Course Content

  1. Business process definition, intra- and inter-organizational processes. Process-oriented organizations. Build processes’ business models. Virtual enterprises. Business processes and workflows.
  2. Process analysis techniques. Qualitative process analysis (e.g. Pareto analysis, value-added analysis, root-cause analysis). Quantitative process analysis (e.g. queuing analysis, simulation). Performance metrics (time, cost, quality).
  3. BPM life cycle. Discover, analyze, model, monitor, map, simulate, deploy. Business Process Reengineering-BPR and Business Process Improvement- BPI methodologies. Business Process modeling tools.
  4. The BPMN standard for business process modelling.
  5. Business process automation. Conceptual and executable process models.
  6. Business Processes Management Systems-BPMS (e.g. structure, architecture, standards).
  7. Process and activity life cycles. Workflow-based applications.
  8. Business processes and workflows, workflow categories, workflow dimensions, workflow management, workflow functional requirements, workflow specifications and execution languages.
  9. Workflow management using a specific BPMS software tool.
  10. Process Analytics. Metrics for evaluating business processes’ performance. Monitoring of standard metrics and process specific, user dined metrics.
  11. BPM methodologies (e.g. Six Sigma, Lean).
  12. Service-oriented and process-oriented information systems.

Suggested Bibliography

  • John Jeston and Johan Nelis (2008): Business Process Management, Second Edition: Practical Guidelines to Successful Implementations, Butterworth-Heinemann, Boston, ISBN: 0750669217.
  • Artie Mahal (2010): How Work Gets Done: Business Process Management, Basics and Beyond, Technics Publications, New Jersey, ISBN: 193550407.
  • Matias Weske, (2010): Business Process Management: Concepts, Languages, Architectures, Springer, New York, ISBN: 3642092640.
  • Simha Magal and Jeffry Word (2009): Essentials of Business Processes and Information Systems, Wiley, New York, ISBN: 0470418540.
  • Howard Smith and Peter Fingar (2003): Business Process Management: The third wave. Meghan Kiffer, ISBN: 0929652339.
  • Mark McDonald, (2010): Improving Business Processes, Harvard Business Review Press, Boston, ISBN: 142212973.
  • Business process management Journal, Emerald.
  • International Journal of Business Process Integration and management, Inderscience Publishers.