Students must be able to:
1. Describe the assumptions of the Cognitive Theory of Multimedia Learning (dual channel, limited capacity and active processing);
2. Describe the role of the mnemonic system in multimedia learning;
3. Describe and apply the 5 processes of the Cognitive Load Theory of Multimedia Learning;
4. Interpret the way in which human beings process information from images, narrated and printed words;
5. Define cognitive load and distinguish the different types;
6. Know strategies to efficiently manage cognitive load;
7. Plan a multimedia project starting from the definition of objectives, resources and scheduling and task management;
8. Develop prototypes detailing navigation schemes and content;
9. Test and validate a multimedia product.

1. Memory concepts:
* work
* long term
* interaction between MT and MLP
* learning (cognitivist perspective)
2. Concepts of:
* Communication
* Multimedia
3. Multimedia Learning Theory
4. Multimedia Learning Process
5. Principles of multimedia learning
6. Cognitive Load Theory
7. Multimedia presentations
8. Educational videos according to Multimedia Learning Theory
9. Design, production and evaluation of multimedia projects in an educational context

Students decide by the 2nd class the method of assessment for the 1st period, which can be: periodic assessment or final exam.
In the form of periodic assessment (only for the 1st season) students carry out:
- several tasks carried out in groups 20% (minimum 8.5)
- an individual written test 20%
- a final project 60%
In the final exam modality (available for the 1st season, 2nd season and special season), the final presencial exam corresponds to 100% of the final grade.

By the end of this course unit, the student should be able to:
LO1: Apply fundamental programming concepts.
LO2: Create procedures and functions with parameters.
LO3: Understand the syntax of the Python programming language.
LO4: Develop programming solutions for problems of simple complexity.
LO5: Explain, execute, and debug code fragments developed in Python.
LO6: Interpret the results obtained from the execution of code developed in Python.
LO7: Develop programming projects.

S1. Introduction to Programming: Logical sequence and instructions, Input and output of data, Constants, variables, and data types, Logical, arithmetic, and relational operations, Control structures
S2. Procedures and Functions
S3. References and Parameters
S4. Integrated Development Environments
S5. Syntax of the programming language
S6. Objects and object classes
S7. Lists and Lists of Lists
S8. File Manipulation

The course unit follows a project-based assessment model due to its highly practical nature and does not include a final exam.
Students are evaluated based on the following parameters:
A1: Programming tasks validated by the instructors (10%), with a minimum grade of 9.5 out of 20 in the average of the tasks.
A2: Individual Project with theoretical-practical discussion (40%), with a minimum grade of 8.5 out of 20.
A3: Group Project with theoretical-practical discussion (50%), with a minimum grade of 8.5 out of 20.

LG1 Represent points and vectors and calculate distances.
LG2 Perform operations with vectors and identify the relative position of planes and lines.
LG3 Determine equations of the line and the plane.
LG4 Calculate and interpret the inner and cross products between vectors.
LG5 Parametrising curves and calculating normal and tangent vectors.
LG6 Identify the different conics and make its representation.
LG7 Understand the properties of triangles and apply them to solve problems.
LG8 Distinguish between population and sampling and classify variables.
LG9 Represent and analyse data and apply and interpret statistical measures.
LG10 Apply statistical inference measures and hypothesis tests.
LG11 Understand and apply the concept of distribution.
LG12 Acquiring skills in problem solving contextualized in topics of the course.
LG13 Articulate the different approaches of the contents: graphical, numerical and algebraic.

PC1 Points and vectors in the plane and in space
PC2 Distance between two points and from a point to a line. Planar sections and spherical surface. Measures
PC3 Vectors and operations. Inner product. Parallelism and perpendicularity of vectors. Relative position of lines and planes
PC4 Vector director and equation of a line
PC5 Cross product. Vector normal to a plane and equations of the plane
PC6 Parametrization of curves in plane and in space. Normal and tangent vectors to a curve. Intersection of curves. Polar coordinates
PC7 Conics (parabolas, hyperbolas, circles and ellipses) and study of triangles
PC8 Quantitative and qualitative variables in statistics. Data grouped into classes
PC9 Relative and absolute frequencies. Measures of location. Dispersion parameters. Correlation coefficients
PC10 Basic concepts in inferential statistics. Estimation. Confidence intervals
PC11 Hypothesis testing
PC12 Random variable and probability distributions (normal, Student's t, chi-square).

Approval with a mark of not less than 10 (scale 1-20) in one of the following modalities:
- Periodic assessment: 2 assessment tests (T1 and T2) (25% each) + weekly exercises (10%) + final test (FT) taken on the date of the first exam (40%).
The average mark for the tests ( (T1+T2)/2 ) is at least 7.0.
The final test (FT) has a minimum mark of 7.0.
or
- Assessment by Exam (100%).

LO1: To know the main concepts related to Learning Psychology.
LO2: To understand the main psychological processes associated with academic success as well as learning difficulties.
LO3: To analyze the teaching-learning process in the light of theoretical proposals from Learning Psychology.
LO4: To explore the school context as a primary field of intervention for Learning Psychology.

CP1: Introduction to Learning Psychology
CP2: Concepts of Learning Psychology and Object of Study
CP3: Main Theories of Learning Psychology:
(Behaviorism, Cognitivism, Humanism, Socio-constructivism, and Connectivism)
CP4: Conceptions of Memory in Learning
CP5: Applications of Memory in Educational Practices
CP6: Concept of Motivation
CP7: Motivational Guidance of Students for Learning
CP8: Strategies to Promote Motivation for Learning
CP9: Learning Strategies in the School Context
CP10: Learning Difficulties
CP11: Learning Psychology and Bullying

Periodic assessment (only available in Season 1):
Completion of 4 mini-tests at the end of each module. Each mini-test accounts for 5% of the final grade, with a minimum score of 8 points. Completion of a group project, distributed over 3 assessment moments, with a minimum score of 7.5 points in each one, representing 45% of the final grade. Tasks/assignments to be completed, either in pairs or groups, in the classroom and in autonomous work, representing a total of 35%, with a minimum score of 7.5 points. The average of the assessments must be equal to or greater than 9.5 points.

Assessment by exam (Season 1 if the student chooses, Season 2 and Special Season):
Face-to-face exam (100% of the final grade)

After successfully attending the curricular unit, students should be able to:

OA1. Know the different data formats.
OA2. Know the complete data cycle.
OA3. Know how to perform exploratory data analysis using R.
OA4. Know how to model a set of data.
OA5. Implement a data analysis solution for a given problem.

CP1. Introduction to Data Analysis
CP2. Introduction to R and RStudio
CP3. Knowledge of problems in data analysis with examples
CP4. The complete cycle of data analysis
CP5. Data and data format
CP6. Data preparation
CP7. Odds; Descriptive Statistics and Exploratory Analysis
CP8. Data visualization
CP9. Modeling and different types of machine learning problems
CP10. Model evaluation methods
CP11. Reporting and publishing results

PERIODIC assessment results from: online exercises, without a minimum grade, after each class (20%); two individual tests - a mid-term test and another at the end of the semester (30%); and a group work (maximum of 3 students) in R with preparation of a report and oral presentation (50%).

Students who obtain a final grade above 9.5 are approved.

LO1. Differentiate between direct and indirect teaching methods
LO2. Develop learning objectives based on content and desired outcomes
LO3. Establish learning goals and outcomes from overarching questions
LO4. Identify evidence of learning
LO5. Implement active and blended learning strategies
LO6. Apply classroom observation methods
LO7. Categorize types of feedback
LO8. Create and adapt teaching strategies considering diverse individual and collective student needs

S1. Introduction to direct and indirect teaching methods
S2. Learning objectives
S3. Learning goals and outcomes
S4. Evidence of learning
S5. Active learning
S6. Combined teaching strategies
S7. Classroom observation methods
S8. Feedback
S9. Organization of the teaching-learning process

Season 1: Until the second class, the student chooses whether to be assessed through periodic evaluation or examination.
Periodic Evaluation: Tasks (10%), with a minimum grade of 9.5, Case Study Report (70%) with a minimum grade of 9.5, and Test (20%) with a minimum grade of 8.5.
Examination Assessment: Exam (100%) with a minimum grade of 9.5.
Season 2: Exam (100%) with a minimum grade of 9.5.
Special Season: Exam (100%) with a minimum grade of 9.5.

The objective of the UC is to develop a technological project in line with the scope of the Course. Contact will be established with project planning considering the main phases: Requirements analysis, development, partial tests and final tests and changes. Contact with laboratory equipment and tools is one of the goals for designing a software, hardware or both project.

I. Introduction to technological innovation along the lines of Europe
II. Planning a technological project and its phases
III. Essential aspects for the development of a project
IV. Definition of material resources
V. Budget of a project
VI. Partial and joint Test Plan
VII. Presentation of a technological project
VIII. Technological project demonstration
IX. Preparation of Technical Report

Periodic grading system:
- Group project: first presentation: 30%; second presentation and exibithion: 40%; final report: 30%. The presentations, demonstrations and defence are in group.

OA1 - Understand basic concepts of composition, structure and construction of graphic elements.
OA2 - Understand the differences between vector image and bitmap image.
OA3 - Mastering basic rules of graphic communication.
OA4 - Mastering techniques and tools for producing vector graphics.
OA5 - Mastering techniques and tools for bitmap image production.
OA6 - Be able to create, process or manipulate a graphic image.
OA7 - Master text formatting techniques.
OA8 - Be able to combine image and text in order to create a graphic element.
OA9 - Mastering techniques for constructing a graphic narrative.
OA10 - Know and apply different formats when exporting graphic elements.
OA11 - Mastering basic concepts of web design and publishing images online.

CP1. Composition, structure and construction of the graphic form.

CP2. Vector Drawing:
- Principles and concepts;
- Drawing tools and techniques;
- Text formatting. Principles of composition and typographic rigor;
- Construction and use of grids;
- Use of vector elements.

CP3. Bitmap Painting:
- Basic notions and concepts (pixel);
- Image size, resolution and compression;
- Image Modes - Use and mastery of color channels;
- Tools and techniques for painting and drawing;
- Image creation, manipulation and treatment;
- Creation of synthetic and simulation images;
- Text composition (?Bitmap Text? vs ?Vector Text?).

CP4. Creation of static Digital Educational Resources:
- Composition of the graphic narrative in an educational and training context: relationship between concept, image, text and support;
- Graphic elements in educational interventions.

Assessment will be continuous, implying a minimum presence of 75% in class, with students being assessed in different dimensions, according to their involvement in the work production processes, the interest shown in the various subjects and their capacity to produce the various contents that must be requested throughout the UC. The final grade results from the weighting: 80% projects + 15% engangement in activities + 5% presence in classes.

LO1: Know the main theories, concepts and problematics related to Work, Organizations and Technology;
LO2: Understand the main processes of the digital transition directly related to the world of work and its organizations;
LO3: Analyze the multiple social, economic and political implications of the digital transition;
LO4: Explore cases, strategies and application methods to understand the real impacts of the digital transition on professions, companies and organizations.

S1. Is work different today than in the past? S2. How has theory looked at technology?
S3. What technologies for the future?
S4. What future for work?
S5. How intelligent is artificial intelligence?
S6. Where does precarity begin?
S7. Do platform workers need employment contracts?
S8. Who is to blame when the machine goes wrong?
S9. Are digital technologies changing the relationship between unions and companies?
S10. Does teleworking make people happier?
S11. Portugal and the digital transformation?

"Periodic evaluation:
Making of an Inverted class class. Each Inverted Class represents 20% of the final mark, with a minimum mark of 8. Weekly question and answer which represents 10% of the final mark, with a minimum mark of 8. An individual assignment, spread over 3 assessment periods, with a minimum mark of 8 in each, representing 35% of the final grade. A group assignment, representing a total of 35% (10% group presentation and 25% written assignment), with a minimum mark of 8. The average grade must be equal to or greater than 9.5.

Assessment by exam (First season 1 if the student chooses, Second Season and Special Season): In-person exam (100% of the final grade)."

Learning Outcomes:
LO1. Develop oral communication skills
LO2. Improve body expression
LO3. Master the art of using the vocal apparatus
LO4. Learn performance techniques

Compatibility with the Teaching Method:
The course combines theory and practice, providing students with an immersive experience in the world of public performances with theatrical techniques. The teaching method is interactive and participatory, encouraging students to put into practice the concepts learned through individual and group exercises.

The knowledge acquired involves both theatrical theory and specific oral communication techniques. Participants will learn about the fundamentals of vocal expression, character interpretation and improvisation, adapting these skills to the context of public presentations

S1 - Preparation for presentation (3 hours)
S2 - Non verbal communication (3 hours)
S3 - Introduction to using the vocal apparatus (3 hours)
S4 - Introduction to the term Performance (3 hours)

Modality of continuous assessment:
Practical Presentations (50%): Participants will be assessed based on their public presentations during the course. Criteria such as clarity of communication, vocal and body expression, use of theatrical techniques and performance will be considered. Presentations may be individual or group presentations, depending on the activities proposed.

Exercises and Written Assignments (50%): In addition to the practical presentations, participants may be asked to complete exercises and written assignments related to the content covered in each module. These may include reflections on learned techniques, analysis of case studies, answers to theoretical questions or even the creation of presentation scripts. These activities will help to assess participants' conceptual understanding.

To conclude the curricular unit in the modality of continuous assessment the student must be present in 75% of the classes.
Although not recommended, students may opt for final assessment by written and oral examination (100%).

LO1. Acquiring knowledge about the fundamentals and stages of the Design Thinking process
LO2. Develop skills such as critical thinking, collaboration, empathy and creativity.
LO3. To apply Design Thinking in problem solving in several areas, promoting innovation and continuous improvement.

S1. Introduction to Design Thinking and Stage 1: Empathy (3h)
S2. Steps 2 and 3: Problem Definition and Ideation (3h)
S3. Step 4: Prototyping (3h)
S4. Step 5: Testing and application of Design Thinking in different areas (3h)

Modality of continuous assessment:
Class participation (20%): evaluates students' presence, involvement and contribution in class discussions and activities.
Individual work (40%): students will develop an individual project applying Design Thinking to solve a specific problem. They will be evaluated on the application of the stages of Design Thinking, quality of the proposed solutions, and creativity.
Group work (40%): students will form groups to develop a joint project, applying Design Thinking to solve a real challenge. Evaluation will be based on the application of the steps of Design Thinking, quality of the solutions and collaboration among group members.

To conclude the curricular unit in the modality of continuous assessment the student must be present in 75% of the classes.
Although not recommended, students may opt for final assessment by written and oral examination (100%).

"LO1. Knowledge about the structure, language, ethical and normative procedures for the elaboration of academic texts.
LO2. Skills to use generative algorithms to assist the elaboration of academic work.
LO3. Skills in analysing and scrutinising the independence, relevance and reliability of AI generated data.
LO4. Overall abilities to recognise the ethical and civic implications underlying the access, sharing and use of AI tools in an academic context."

"S1. Introduction to Academic Writing and generative algorithms (3h)
S2. Procedures for planning and constructing argumentative texts with the aid of AI (3h)
S3. Critical analysis of texts produced: identification and referencing of data sources and analysis of their relevance in the ligth of the objectives of the academic work (3h)
S4. Opportunities and risks of AI use: good practice guide for accessing, sharing and using AI tools in an academic context (3h)"

"Modality of continuous assessment:
Class participation: Class participation: assesses students' attendance, involvement and individual contributions to class discussions and activities (20%).
Group work will require students to form groups to revise and edit academic texts between themselves, using generative algorithms. Assessment will be based on the quality of the revisions, edits and feedback provided (40%).
Individual report: with an in-depth reflection on the civic and ethical questions posed by the use of AI tools as an aid to academic writing (40%).
There is a required minimum of 7 values in each component that is graded.

To conclude the curricular unit in the modality of continuous assessment the student must be present in, at least, 75% of the classes.
Although not recommended, students may opt for final assessment by written and oral examination (100%).

In addition to the practical presentations, students will be asked to carry out exercises and written tasks related to the content covered. These may include: reflecting on techniques learnt, analysing case studies, answering theoretical questions or even creating presentation scripts. These activities will help to assess conceptual understanding of the content taught.

LO1 Know the basic principles of Information Systems and their role in organizations
LO2 Know the fundamental concepts of Information Systems Analysis and develop semantic (conceptual) models for systems described in text, through practical application of the UML language, and understand the conversion of such conceptual models into relational database models (RDBs)
LO3 Know how to model and design a Relational DB (RDB), with the Relational Model
LO4 Know the normal forms and relational algebra and understand the normalization of an existing RDB based on performance metrics
LO5 Know how to create and modify the physical structure of a RDB using SQL
LO6 Know how to use, at an elementary level, the administration tools associated with a Database Management System (DBMS)
LO7 Develop self-learning, peer review, teamwork, oral and written expression

S1 Introduction to Information Systems and its role in organizations
S2 Introduction to Information Systems Analysis with UML language: requirements analysis, data models, schemas and UML diagrams
S3 Database Design. Relational Model: relationships, attributes, primary keys, foreign keys, integrity rules, optimizations and indexes
S4 Normalization. Redundancy and inconsistency of data. Normal forms
S5 SQL Language - Table variables, set operators, simple queries, subqueries, operators (SELECT, Insert, delete, update), views, indexes, triggers, stored procedures and transactions
S6 Introduction to Database Management Systems administration, DBMS

Periodical Assessment:
- 1 test to be done in the middle of the semester (30%)
- 1 test to be taken in the 1st season of exams (30%)
- 1 modelling and implementation project (40%)

Both tests have a minimum grade of 8 values and the project is mandatory for approval.

Assessment by exam:
-1 Written exam weighted at 100%

The minimum grade for approval in this course is 10 values.

At the end of the learning unit, the student must be able to: LG.1. Understand entrepreneurship; LG.2. Create new innovative ideas, using ideation techniques and design thinking; LG.3. Create value propositions, business models, and business plans; LG.5. Develop, test and demonstrate technology-based products, processes and services; LG.6. Analyse business scalability; LG.7. Prepare internationalization and commercialization plans; LG.8. Search and analyse funding sources

I. Introduction to Entrepreneurship;
II. Generation and discussion of business ideas;
III. Value Proposition Design;
IV. Business Ideas Communication;
V. Business Models Creation;
VI. Business Plans Generation;
VII. Minimum viable product (products, processes and services) test and evaluation;
VIII. Scalability analysis;
IX. Internationalization and commercialization;
X. Funding sources

Periodic grading system: - Group project: first presentation: 30%; second presentation: 30%; final report: 40%.

The Training Management course will adopt a student-centered teaching method through project-based learning, combined with individual task-based learning. In the group work, higher-level skills are promoted, such as analyzing, creating, and evaluating a digital training project. By the end of the course, students will be able to:
LO1: Characterize different training types, modalities, and products
LO2: Identify qualification systems and competency frameworks
LO3: Conduct a training needs assessment
LO4: Design a training program based on the needs assessment of an organization or market
LO5: Develop technical and pedagogical tools for training facilitation
LO6: Produce digital content for training
LO7: Plan, execute, and evaluate training

S1: Training Concepts, Types and Modalities
S2: Digital Training: Tools and Platforms
S3: Qualification Systems and Competency Frameworks
S4: The Training Cycle
S5: Training Accreditation: Standards and Certification

A1: Individual tasks throughout the semester, which constitutes a students' portfolio, following the criteria defined by the instructor, account for 40% of the final grade, with a minimum passing grade of 7.5.
A2: Assessment by project, following the General Regulation for the Assessment of Knowledge and Competencies at ISCTE. The group Project carries a weight of 60% in the final grade, with a minimum passing grade of 7.5.

The final average grade must be equal to or higher than 9.5.
There is no exam assessment in this course unit.

At the end of this course, the student should be able to:
LO1. Understand cybersecurity in its different perspectives
LO2. Understand the main security challenges and threats that organisations and users have to face;
LO3. Introduce the legal, ethical and strategic context of information security
LO4. Identify and manage information security risk;
LO5. Know and apply appropriate security technologies for risk mitigation;
LO6. Know mechanisms for the management and maintenance of information security environments.

SC1. Introduction to Cybersecurity: main components; cybersecurity pillars; cybersecurity frameworks.
SC2. Information Security Planning and Legal and Ethical Framework
SC3. Principles of Information Security Governance and Risk Management
SC4. Introduction to Information Security Technology: access controls, firewalls, vpns, idps, cryptography and other techniques.
SC5. Physical Security: physical access control mechanisms, physical security planning, among others.
SC6. Information Security Implementation: information security project management; technical and non-technical aspects of information security implementation.
SC7. Personnel Security: personnel security considerations; personnel security practices.
SC8. Maintenance of Information Security.

Periodic Assessment:
- Realisation of a set of group projects and activities (60%) throughout the semester
- Two individual tests (40%) [minimum score of 6 points for each test].
Attendance of a minimum number of classes is not compulsory in Periodic assessment.
Assessment by examination:
For students who opt for this process or for those who fail the periodic assessment process, with 3 epochs under the RGACC.

OA1 - Mastering basic script production techniques.
OA2 - Having the hability to produce a storyboard.
OA3 - Know how to organize information with a view to audiovisual production (photography and video).
OA4 - Master basic image capture techniques.
OA5 - Master several techniques and tools to produce animation and motion design.
OA6 - Being able to produce animated sequences and visual narratives.
OA7 - Develop basic notions of sound capture.
OA8 - Master video editing techniques.
OA9 - Know how to export and publish animated content in different formats and media.

CP1. Introduction to animation and motion design techniques and technologies.
CP2. Basic principles and concepts of animation
- Timeline
- FPS
- Keyframes
- Animation curves
- Modeling and rigging (3D animation)
CP3. Creating animated sequences
CP4. visual narratives
CP5. vector files
CP6. Pre-compositions
CP7. masks
CP8. Motion Tracking
CP9. rendering
CP10. Basic principles of sound capture, video editing and export

Assessment will be continuous, implying a minimum presence of 75% in class, with students being assessed in different dimensions, according to their involvement in the work production processes, the interest shown in the various subjects and their capacity to produce the various contents that must be requested throughout the UC. The final grade results from the weighting: 80% projects + 10% involvement in activities + 10% progression.

By successfully completing this CU, the student will be able to:
LO1. Evaluate and select platforms for management and distribution of educational and training content;
LO2. Install, configure, customize and manage platforms for content management
LO3. Create learning content for distance training and learning courses
LO4. Plan and execute the distance learning courses design within the pedagogical and technical approach
LO5. Organise, construct and implement courses in content/learning management platforms

PC1. Characterization and selection of platforms for management and distribution of learning content
- Learning Management Systems (LMS)
- Content Management Systems (CMS)
- Virtual Learning Environments (VLE)
PC2. Employment of LMS platforms
- Installation
- Configuration
- Management
- Customization
- Content creation and management
PC3. Development of distante learning courses
- Pedagogical design
- Instructional design models
- Planning and development of activities and learning and evaluation resources
PC4. Production and assessment of e-content: context, content, functionality and relevance

Students are evaluated at 100% through a project, that includes a report of all phases, in the following way:
First Period: Group Project (70%) , according to the following steps:
a) Configuration and personalization of a LMS (40%);
b) Design and development of a course (30%);
c) Production of e-content (30%).
Individual discussion in the regular period (30%).
A minimum grade of 7,5 points is required in each phase of the project, including in the final discussion. The total average to pass the CU needs to be equal to or more than 9,5 points.

Second and Special Period: individual project (100%)

LO1: Understand the historical context of Computing and HCI (Human-Computer Interaction) and the principles of user-centred Design
LO2: Understand the fundamental perceptive and cognitive characteristics of human beings and their respective limitations that impact HCI design.
LO3: Create empathy with the user (needs, goals, current and desired tasks, problems). Requirements based on collected data.
LO4: Apply principles and 'golden rules' of HCI design and usability in practical cases
LO5: Apply techniques/rules of visual screen design (WWW and mobility). Create storyboards and low-fidelity (Lo-Fi) and high-fidelity (Hi-Fi) prototypes. Perform ideation and development of the Minimum Viable Product (and its Lo-Fi).
LO6: Design and apply heuristic evaluation with Lo-Fi experts, leading to a new iteration and Hi-Fi development.
LO7: Design experimental studies of the Hi-Fi with end-users and apply usability and task satisfaction metrics based on collected data.

S1: Introduction, Program, and Assessment. Computing and HCI: History, state-of-the-art, and applications
S2: User-centered design process. We, the Humans
S3: User and task analysis. Empathy map. Personas. User "as is" scenarios and journeys. User questions. User requirements
S4: Principles and golden rules of interface design. Usability
S5: Visual design of screens (WWW, mobility)
S6: Ideation. Storyboards. Prioritization. Low-fidelity (Lo-Fi) and high-fidelity (Hi-Fi) prototypes of the solution
S7: Deliver a functioning solution. Heuristic evaluation with experts. User evaluation. Statistical analysis of evaluation data. Calculate metrics and iterate the design. Requirements of an MVP (Minimum Viable Product). Elevator Pitch to investors and users

Course under Periodic Assessment, not including a Final Exam. Weights:
70% Group lab project work + presentation and discussion.
30% Two multiple-choice mini-tests
In the second Exam period, mini-tests with a score of 7.5 or lower must be retaken. If the student fails the regular period (score < 10), is eligible to take the exam in the 2nd or special seasons (which counts for 30% of the grade). Need to pass the group project or an equivalent individual project (70% of the grade) is mandatory

At the end of this course students should be able to:
LO1. Define curriculum and associated dimensions;
LO2. Frame narratives in different theories about the curriculum;
LO3. Understand the role of curriculum agents and structures;
LO4. Describe curriculum development models;
LO5. Apply the principles of curriculum development and curriculum management models;
LO6. Propose curricular innovation measures;
LO7. Plan curriculum evaluation strategies;
LO8. Analyze practical curriculum planning situations in different contexts;
LO9. Plan an investigation in the context of curriculum development;
LO10. Design and apply qualitative data collection instruments (semi-structured interviews).

1. Theoretical foundations of the curriculum
- What is the curriculum;
- Dimensions associated with the curriculum;
- Curriculum theories;
- Agents and structures: from local to global.
2. Curriculum Development
- What is Curriculum Development?
- Curriculum management;
- Curriculum development models;
- Curricular innovation;
- Curricular Assessment (objectives and objects of assessment, internal/external/mixed, assessment methods and techniques).
3. Curricular Planning in Education and Training
- Basic and secondary education;
- Professional education;
- University education.

Students decide by the 2nd class the method of assessment for the 1st season, which can be: periodic assessment or final exam.
In the periodic assessment modality (1st season) students prepare an individual digital portfolio (40%), with a minimum grade of 8.5, and carry out group research work (60%), with a minimum grade of 8.5. The weighted average between the individual digital portfolio and the group research work must be equal to or greater than 9.5.
In the final exam modality (available for the 1st season if the student chooses, 2nd season and special season), the face-to-face final exam corresponds to 100% of the UC's final grade.

At the end of this UC, the student should be able to:
LG.1. Present the image of the product/service in a website
OA.2. Present the image of the product/service in social networks
OA.3. Describe functionalities of the product/service
OA.4. Describe phases of the development plan
OA.5. Develop a prototype
OA.6. Test the prototype in laboratory
OA.7. Correct the product/service according to tests
OA.8. Optimize the product/service considering economic, social, and environmental aspects
OA.9. Adjust the business plan after development and tests, including commercialization and image
OA.10. Define product/service management and maintenance plan

I. Development of the product/service image
II. Functionalities of the product/service
III. Development plan
IV. Development of the product/service (web/mobile or other)
V. Revision of the business plan
VI. Management and maintenance of the product/service
VII. Certification plan
VIII. Intellectual property, patents, and support documentation
IX. Main aspects for the creation of a startup - juridical, account, registry, contracts, social capital, obligations, taxes

Periodic grading system:
- Group project: first presentation: 30%; second presentation: 30%; final report: 40%. The presentations, demonstrations and Defence are in group.

LO1 Frame and understand the main components of the World Wide Web;
LO2 Know and correctly apply the client programming model and the MVC paradigm;
LO3 Use and extend server technologies to develop web applications and services;
LO4 Integrate web applications and services with Database Management Systems;
LO5 Understand the life cycle pipeline of a web project;
LO6 Develop creativity, technological innovation, critical thinking;
LO7 Develop self-learning, peer review, teamwork, oral expression.

S1 Introduction. The history of the Web. Programming languages for the Web; W3C standards.
S2 World Wide Web Architecture. Screen marking with HyperText Markup Language (HTML).
S3 Client-side programming. Structure description (HTML), style sheets (CSS) and dynamic updating of the graphical interface. Input validation; Introduction to client-side security.
S4 Server-side programming. Distribution of static content, dynamic generation of content and MVC design pattern. Services and communication between services. Introduction to server-side security.
S5 Data persistence. Integration with Database Management Systems
S6 Service-oriented web architectures. Web Services and Microservices. Middleware models for the Web. Containerization.

Course with Periodic Assessment, not by Final Exam.
Assessment weights:
- Lab project (in group between 2 and 4), with technical report, individual oral discussion (60%)
- 4 multiple response individual Mini-tests (40%)

A mark below 8 assigns (in average of mini-tests) the student to an exam in normal and/or the appeal period (40% of the mark) in a written test, with the completion and approval of the group project, or an individual project (with technical report and individual oral discussion) is mandatory (60%).

LO1: Distinguish the different types of disabilities and associated characteristics
LO2: Identify Universal Design Principles and Inclusive Design Practices
LO3: Know the main functional challenges of assistive technologies
LO4: Apply accessibility practices to digital content
LO5: Develop accessible and inclusive digital educational resources, depending on the context

S1: Main types of disability: visual, auditory, motor and cognitive
S1.1: Special Education Disabilities
S2: Universal design: principles and applications in learning.
S2.1: Inclusive design practices
S3: Functional challenges of assistive technology
S4: Accessibility applied to digital content: text, audio, complex images, videos, graphics and tables
S4.1: Document conversion, subtitling, audio description, accessible document design.
S5: Accessible and inclusive digital content for web in educational context: definition of usability goals and measures, content control, writing of customized accessible components

Continuous assessment: project (60%) and theoretical-practical test (40%), or Final assessment: exam (100%)

At the end of the course, the student should be able to:
LO1: Apply co-creation methodologies in the development of innovative triple sustainable projects (with economic, social and environmental value) in organizations.
LO2: Create empathy with the user and his organization (define needs, obstacles, goals, opportunities, current and desired tasks), define the problem and raise the issues addressed by the project.
LO3: Conduct a systematic literature review and competitive landscape analysis (if applicable), related to the identified problem and the issues raised.
LO4: Identify the digital (including data collection), computational and other resources needed to address the problem.
LO5: Apply already consolidated knowledge of project planning, agile management and project development, within the framework of group work.
LO6: Participate in collaborative and co-creation dynamics and make written and oral presentations, in the context of group work.

S1 Co-creation methodologies based on Design Thinking and Design Sprint
C2 Sustainable Development Goals (SDGs) of the United Nations. Creation of value propositions
S3 Presentation of case studies and digital technologies project topics in education (product, service or process)
S4 Selecting the project topic and framing it in the organization
S5 Problem space: creating empathy with the user and his organization, defining the problem and its related issues, considering business requirements, customer and user needs, and technology challenges
S6 Application of a systematic literature review methodology and its critical analysis. Competition analysis (if applicable)
S7 Identification of digital resources (including data collection), computational, and other resources required for project development
S8 Application of agile project management methodologies, appropriate to the group work to be developed by the students of the education area. Communication of results.

Course in periodic assessment, not contemplating final exam, given the adoption of the project-based teaching-learning method applied to real situations. Presentations, demonstrations and discussion will be carried out in groups.
Assessment weights:
R1 Report: Project Topic Definition: 5%.
R2 Report: Empathy with the User and the Organization and Definition of the Problem. Its presentation and group discussion: 40%
R3 Report: Systematic Literature Review and Project Development Planning. Its presentation and group discussion: 55%.

The aim is to introduce the concepts and practical knowledge fundamental to the design and implementation of an analytical information system for an organization:
(LO1) Plan and manage the life cycle of a data warehouse project, logical and physical design;
(LO2) Identify requirements and data sources and design an appropriate dimensional model;
(LO3) Model an Analytical Information System;
(LO4) Design and implement a data extraction, transformation and loading process;
(LO5) Analyze data in a data warehousing system , have an understanding of Business Intelligence and its applicability; what are standard reports and performance indicators ( KPIs );

(CP1) SQL review: simple queries. Union of tables. Ordering. Grouping and aggregation.
(CP2) Data integration, introduction to ETL tools: data sources. Data integration using visualizations. Data integration versus data warehousing. ETL process. ETL tools.
warehouse design : OLAP operations in SQL. Multidimensional model. Modeling in UML. Typical OLAP operations on a data cube. Data warehouse schema types . Hierarchies and types of hierarchy. Measurements.
(CP4) The OLAP Cube and MDX queries - Data storage and OLAP cubes. OLAP server. OLAP cube definition. OLAP interface. Analysis queries. SQL versus MDX. MDX Concepts.
(CP5) Reporting tools and ( KPIs ) - Data warehousing architecture overview . OLAP tools: front-end and MDX queries . Reporting tools. Reports via SQL and MDX queries. Key performance indicators ( KPIs ). Visualization with dashboards .

Periodic assessment results from the following components:

- A midterm test (20% of the final grade) and another at the end of the semester (20% of the final grade);

- Group work (maximum 3 students) in which the group will develop an analytical information system with the writing of a report which involves 3 deliverables to be submitted along the semester(30% of the final grade, 10% each deliverable) and an oral presentation with a demonstration of the operation of the developed application and discussion (30% of the final grade).

Alternatively, students may choose to be assessed in a final exam (100% of the final grade)

Students who obtain a final grade above 9.5 are approved.

LO1: To know the definition and areas of AI and Machine Learning
LO2: To know the definition of intelligent agent and its characteristics
LO3: To identify the various components of an Intelligent Tutor System
LO4: To identify and apply the best representation of knowledge in ITS
LO5: To identify and apply the best inference and diagnosis methods
LO6: To identify and apply conversation and recognition methods for student-computer interaction
LO7: To identify and apply forms of Interaction Human - AI for collaboration and tutoring
LO8: To identify methods for the personalization and adaptation of educational content
LO9: To apply IA techniques for the evaluation of the learning process
LO10: Identifying the principles of a responsible and trustworty AI

SC1: Introduction to Artificial Intelligence and Machine Learning
SC2: Introduction to Intelligent Agents
SC3: Intelligent Tutoring Systems
SC3.1: ITS Components
SC3.2: Learner Modeling
SC3.3: Knowledge Representation and Inference
SC4: Conversation Agents and Virtual Tutors
SC5: Human-AI Collaboration
SC6: Intelligent Content Generation and Management
SC7: Analysis of Educational Data
SC8: AI in Education - Ethical and Responsible

Students are evaluated at 100% through the project in the following ways:
Regular Period: Project carried out in groups of students throughout the semester and accompanied by tutoring classes (12 hours) (60%). Individual discussion in the 1st evaluation period (40%).
Repeat and Special Period: individual project (100%)

LO1: Correct the user and/or organization problem identified in the Applied Project I course of the 1st semester, developing, in an iterative way, an integrated project with all its components, including requirements gathering, solution prototyping (lo-fi, hi-fi, MVP), and evaluation and field deployment of the innovative solution, regarding product, process or service (PPS).
LO2: Produce design documentation of the PPS innovation solution, including, where applicable, architecture, hardware and software configuration, installation, operation and usage manuals.
LO3: Produce solutions with the potential to be triple sustainable in the field, taking into account the applicable legal framework.
LO4: Produce audiovisual content on the achieved results, to be exploited in several communication channels: social networks, landing page web, presentation to relevant stakeholders, demonstration workshop.

S1 Solution space: ideation of the best technological solution relative to the project, development of user requirements, storyboarding, user/costumer journey, iterative prototyping cycles (low fidelity - lo-fi, high fidelity - hi-fi, minimum viable product - MVP), heuristic evaluation of the solution with experts and evaluation with end users.
S2 Production of solution design documentation, including, where applicable, architecture, technical specifications, hardware and software configuration, installation, operation and use manuals.
S3. Experimental deployment of the solution with the potential to be triple sustainable (with economic, social and environmental value creation), safeguarding the applicable legal framework.
S4. Audiovisual communication on the Web and social networks. Communication in public and its structure. Presentation to relevant actors.
S5. Demonstration in workshop with relevant actors

UC in periodic assessment, not contemplating final exam, given the adoption of the project-based teaching method applied to real situations. Presentations, demonstrations and discussion are carried out in groups.
Evaluation weights:
R1 Solution Ideation Report, with Storyboard, User Journey, User Requirements, Technical Specifications and its audiovisual presentation: 20%.
R2 Solution Prototyping: Lo-fi and Hi-fi Prototypes and Minimum Viable Prototype - MVP (on GitHub), its Demonstration and Evaluation Report: 40%
R3 Solution Design Report with the following elements (if applicable): Architecture (UML Package Diagram, UML Component Diagram), Hardware and Software Configuration, Installation Manual (UML Deployment Diagram, Configuration Tutorial), Operation Manual, User Manual: 20%
R4 Audio-visual presentation of the solution and its demonstration in a Workshop: 20%.

The student who successfully completes this UC will be able to:
OA1. Identify the main contemporary issues and debates;
OA2. Analyze current issues and debates in a reasoned manner;
OA3. Identify the implications of technological change and digitalization in economic, social, cultural and environmental terms;
OA4. Understand the role and the importance of technology in the challenges of contemporary societies;
OA5. Explore the boundaries between technological knowledge and social science knowledge;
OA6. Develop forms of interdisciplinary learning and critical thinking.

S1. Debates XXI: technological change and contemporary societal challenges.
S2. Digital transition: meaning and implications.
S3. Technology, social change and inequalities.
S4. Environment and transition towards to sustainability.
S5. Globalization, financialisation and development.
S6. Capitalism and democracy.
S7. Migrations and multiculturality.

The periodic assessment process comprises the following elements:
1. Preparation and presentation (class) of a group work on technological change and society (40%).
2. Test (60%).
The final assessment corresponds to 1st and 2nd phase exams (100% of the grade).