Relating Machine Learning to the Real-World: Analogies to Enhance Learning Comprehension

Machine learning is an exciting field for many, but the rigor, math, and its rapid evolution are often found to be formidable, keeping them away from studying and pursuing a career in this area. Similarity has been substantially explored in machine learning algorithms such as in the K-nearest neighbors, Kernel methods, Support Vector Machines, but not so much in human learning, particularly when it comes to teaching machine learning. In the course of teaching the subject to undergraduate, graduate, and general pool of students, the author found that relating the concepts to real-world examples greatly enhances student comprehension and makes the topics much more approachable despite the math and the methods involved. This paper relates some of the concepts, artifacts, and algorithms in machine learning such as overfitting, regularization, and Generative Adversarial Networks to the real world using illustrative examples. Most of the analogies included in the paper were well appreciated by the students in the course of the author’s teaching and acknowledged as enhancing comprehension. It is hoped that the material presented in this paper will benefit larger audiences, drawing more learners to the field, resulting in enhanced contributions to the area. The paper concludes by suggesting deep learning for automatically generating similarities and analogies as a future direction

Teaching Students about Machine Learning Through a Gamified Approach

© 2018 IEEE. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/TALE.2018.8615279The teaching of machine learning requires a range of tools and techniques to engage students and allow them to relate the processes involved to real world situations that they have previously experienced. One way to facilitate this learning process is to integrate the learning into a game situation, which is by definition fun to engage with and offers immediate rewards. This research shows that by collecting the student's behaviour and actions as they engage with well-known game software, the learning of key machine learning concepts can be enabled. It is also shown that customising of learning can be made possible by the use of gamification

Teaching geometrical principles to design students

We propose a new method of teaching the principles of geometry to design students. The students focus on a field of design in which geometry is the design: tessellation. We review different approaches to geometry and the field of tessellation before we discuss the setup of the course. Instead of employing 2D drawing tools, such as Adobe Illustrator, the students define their tessellation in mathematical formulas, using the Mathematica software. This procedure enables them to understand the mathematical principles on which graphical tools, such as Illustrator are built upon. But we do not stop at a digital representation of their tessellation design we continue to cut their tessellations in Perspex. It moves the abstract concepts of math into the real world, so that the students can experience them directly, which provides a tremendous reward to the students

Teaching geometrical principles to design students

We propose a new method of teaching the principles of geometry to design students. The students focus on a field of design in which geometry is the design: tessellation. We review different approaches to geometry and the field of tessellation before we discuss the setup of the course. Instead of employing 2D drawing tools, such as Adobe Illustrator, the students define their tessellation in mathematical formulas, using the Mathematica software. This procedure enables them to understand the mathematical principles on which graphical tools, such as Illustrator are built upon. But we do not stop at a digital representation of their tessellation design we continue to cut their tessellations in Perspex. It moves the abstract concepts of math into the real world, so that the students can experience them directly, which provides a tremendous reward to the students

Técnicas de aprendizaje de máquina y personalización en educación

Las nuevas tecnologías aportan a la educación aspectos innovadores que permiten mejorar las formas de enseñar y aprender. Particularmente, una de las principales innovaciones son los sistemas de educación a distancia, que ofrecen formación continua a estudiantes que por diversas razones no pueden asistir a clases. Como en la enseñanza presencial, en la enseñanza virtual es necesario que los alumnos logren una asimilación efectiva del conocimiento. Sin embargo, frecuentemente tal asimilación no ocurre porque los cursos de e-learning se diseñan sin considerar las características particulares de cada estudiante. Actualmente, los procesos de aprendizaje centrados en el alumno requieren que estos sistemas sean capaces de personalizar la enseñanza a las características y necesidades individuales de cada estudiante. En este artículo se presenta el sub- proyecto "Técnicas de Aprendizaje de Máquina y Personalización en Educación", que tiene por finalidad estudiar los fundamentos conceptuales, metodológicos y técnicos del Aprendizaje de Máquina y la Personalización, y diseñar, desarrollar y evaluar aplicaciones específicas de ambos en el ámbito de la educación. Para esta investigación, es necesario un estudio de tipo exploratorio, descriptivo y, en algunos casos, correlacional, con métodos y técnicas cuantitativas y cualitativas para alcanzar los objetivos propuestos. Las experiencias y los resultados que se obtengan se transferirán y difundirán mediante actividades formales y sistemáticas.Eje: Tecnología informática aplicada en educaciónRed de Universidades con Carreras en Informática (RedUNCI

Técnicas de aprendizaje de máquina y personalización en educación

Las nuevas tecnologías aportan a la educación aspectos innovadores que permiten mejorar las formas de enseñar y aprender. Particularmente, una de las principales innovaciones son los sistemas de educación a distancia, que ofrecen formación continua a estudiantes que por diversas razones no pueden asistir a clases. Como en la enseñanza presencial, en la enseñanza virtual es necesario que los alumnos logren una asimilación efectiva del conocimiento. Sin embargo, frecuentemente tal asimilación no ocurre porque los cursos de e-learning se diseñan sin considerar las características particulares de cada estudiante. Actualmente, los procesos de aprendizaje centrados en el alumno requieren que estos sistemas sean capaces de personalizar la enseñanza a las características y necesidades individuales de cada estudiante. En este artículo se presenta el sub- proyecto "Técnicas de Aprendizaje de Máquina y Personalización en Educación", que tiene por finalidad estudiar los fundamentos conceptuales, metodológicos y técnicos del Aprendizaje de Máquina y la Personalización, y diseñar, desarrollar y evaluar aplicaciones específicas de ambos en el ámbito de la educación. Para esta investigación, es necesario un estudio de tipo exploratorio, descriptivo y, en algunos casos, correlacional, con métodos y técnicas cuantitativas y cualitativas para alcanzar los objetivos propuestos. Las experiencias y los resultados que se obtengan se transferirán y difundirán mediante actividades formales y sistemáticas.Eje: Tecnología informática aplicada en educaciónRed de Universidades con Carreras en Informática (RedUNCI

Técnicas de aprendizaje de máquina y personalización en educación

Las nuevas tecnologías aportan a la educación aspectos innovadores que permiten mejorar las formas de enseñar y aprender. Particularmente, una de las principales innovaciones son los sistemas de educación a distancia, que ofrecen formación continua a estudiantes que por diversas razones no pueden asistir a clases. Como en la enseñanza presencial, en la enseñanza virtual es necesario que los alumnos logren una asimilación efectiva del conocimiento. Sin embargo, frecuentemente tal asimilación no ocurre porque los cursos de e-learning se diseñan sin considerar las características particulares de cada estudiante. Actualmente, los procesos de aprendizaje centrados en el alumno requieren que estos sistemas sean capaces de personalizar la enseñanza a las características y necesidades individuales de cada estudiante. En este artículo se presenta el sub- proyecto "Técnicas de Aprendizaje de Máquina y Personalización en Educación", que tiene por finalidad estudiar los fundamentos conceptuales, metodológicos y técnicos del Aprendizaje de Máquina y la Personalización, y diseñar, desarrollar y evaluar aplicaciones específicas de ambos en el ámbito de la educación. Para esta investigación, es necesario un estudio de tipo exploratorio, descriptivo y, en algunos casos, correlacional, con métodos y técnicas cuantitativas y cualitativas para alcanzar los objetivos propuestos. Las experiencias y los resultados que se obtengan se transferirán y difundirán mediante actividades formales y sistemáticas.Eje: Tecnología informática aplicada en educaciónRed de Universidades con Carreras en Informática (RedUNCI

Teaching methodologies for new information technologies

Trabalho apresentado em 4th International Conference of the Portuguese Society for Engineering Education (CISPEE 2021), 21-23 junho 2021, Lisboa, PortugalNew Information Technologies is a course whose curriculum was developed to fill the need of teaching students with more recent and emerging topics in information technologies. The novelty is the approach taken to group in a single course numerous loosely related subjects and a hybrid problem-based learning teaching methodology. Preliminary empirical evidence encourages us to continue pursuing this approach and we believe that our experiences may help other teachers designing their courses’ teaching methodology.N/

Inteligência Artificial no Design de Comunicação em Portugal: Panorama e Perspetivas

A tecnologia sempre foi sinónimo de inovação na área do design originando inclusivamente mudanças na sua prática projetual. Atualmente, a Inteligência Artificial (IA) está a alterar profundamente a forma como trabalhamos e comunicamos, tendo impacto em inúmeros setores de atividade. No entanto, não há uma investigação considerável sobre a integração da IA no campo do design. Assim sendo, o principal objetivo desta dissertação é compreender como é que a IA é percecionada e tem vindo a ser aplicada no design de comunicação em Portugal. De modo a atingir este objetivo analisámos a perspetiva de um grupo de designers sobre a IA, tentámos perceber como algumas empresas portuguesas de design utilizam a IA, e se os futuros designers, hoje estudantes, têm conhecimento e estão prontos para trabalhar com IA na sua prática profissional. O método qualitativo de investigação utilizado foi o estudo de caso. A recolha de dados foi feita a partir de entrevistas e questionários conduzidos a designers de 10 empresas portuguesas de design de comunicação. Os websites das empresas também foram analisados com o intuito de perceber se existiria algum envolvimento com a IA. Para tentar compreender a perceção dos estudantes foi feito inclusivamente um questionário a 26 alunos de design de comunicação e multimédia da Universidade da Beira Interior, Universidade do Algarve e Universidade de Coimbra. A investigação concluiu que os designers possuem fundamentos básicos de IA, conhecendo as principais vantagens e algumas desvantagens da mesma. No geral, expressam sentimentos positivos quanto à sua utilização no trabalho quotidiano, considerando que será importante para o futuro do design. Aqueles que a utilizam fazem-no durante as verificações de qualidade e na análise de insights dos utilizadores, nas últimas fases do processo de design. Contudo, a maioria dos profissionais opta por não a utilizar devido a diversos fatores, nomeadamente o preço alto dos softwares e hardware, o foco internacional e grande dispersão das ferramentas, ou porque acreditam não fornece a componente empática e humana própria do design. Os entrevistados relataram ainda que sabiam muito pouco sobre uma série de outros tópicos, incluindo o estado dos recursos de IA em Portugal e as competências necessárias para operar com a IA no trabalho quotidiano. Por seu lado, os estudantes de design mostraram ter consideravelmente menos noções de IA do que os profissionais. Uma percentagem considerável dos estudantes afirma nunca ter aprendido conteúdos de IA durante os seus estudos de licenciatura. Dos que aprenderam, nem todos consideram que os conhecimentos adquiridos sobre IA podem ser úteis para o seu futuro trabalho como designers. Esta investigação sugere que os designers experientes valorizam mais a IA do que os estudantes, para além de terem mais conhecimentos sobre o tema. Esta investigação representa um passo em frente no estudo da dicotomia IA e design de comunicação em Portugal.Technology has always been synonymous with innovation in the design field, including changes in its projectual practice. Today, Artificial Intelligence (AI) is profoundly changing the way we work and communicate, impacting numerous industries. However, there’s not considerable research on the integration of AI into the field of design. Therefore, the main goal of this dissertation is to understand how AI is perceived and has been applied in the communication design sector in Portugal. In order to achieve this goal, we analyzed the perspective of a group of designers about AI, we tried to understand how Portuguese design companies use AI, and if future designers, today students, are aware and ready to work with AI in their professional practice. The qualitative research method used was the case study. Data was collected from interviews and questionnaires conducted with designers from 10 Portuguese communication design companies. The companies' websites were also analyzed to understand if there was any mention of AI. To try to understand the perceptions of students, a questionnaire was even given to 26 pupils of communication and multimedia design from the University of Beira Interior, University of Algarve and University of Coimbra. The research concluded that designers have basic fundamentals of AI, knowing the main advantages and some disadvantages of it. In general, they express positive feelings about its use in their daily work, considering it to be important for the future of design. Those who use it do so during quality checks and in the analysis of user insights in the last stages of the design process. However, most professionals choose not to use it due to several facts, namely the high price of software and hardware, the international focus and wide dispersion of tools, or because they believe it does not provide the empathetic and human component proper to design. Respondents also reported that they knew very little about several other topics, including the state of AI resources in Portugal and the skills needed to operate with AI in everyday work. On the other hand, design students were shown to have considerably less notions of AI than professionals. A large percentage of the students affirm having never learned AI contents during their undergraduate studies. Those who have learned, not all consider that the knowledge gained about AI can be useful for their future work as designers. This research suggests that experienced designers value AI more than students, in addition to having more knowledge about the topic. This research represents a step forward in the study of the AI and communication design dichotomy in Portugal