This study is predicated on the belief that there does not now exist, nor will there ever exist, any single theory of learning that is broad enough to account for all types of learning yet specific enough to be maximally useful in practical application. Perhaps this dichotomy is the reason for the apparent gap between existing theories of learning and the practice of instructional design. As an alternative to any supposed grand theory of learning—and following the lead of prominent thinkers in the fields of clinical psychology and language teaching—this study proposes a shift toward principles. It presents a principle-based conceptual framework of learning, and recommends use of the framework as a guide for creating domain-specific theories of learning. The purpose of this study was to review theories of learning in the behavioral, cognitive, constructive, human, and social traditions to identify principles of learning local to those theories that might represent specific instances of more universal principles, fundamentally requisite to the facilitation of learning in general. Many of the ideas reviewed have resulted from, or been supported by, direct empirical evidence. Others have been suggested based on observational or practical experience of the theorist. The ideas come from different points in time, are described from a variety of perspectives, and emphasize different aspects and types of learning; yet there are a number of common themes shared among them regarding the means by which learning occurs. It is hypothesized that such themes represent universal and fundamental principles of learning. These principles were the objective of the present study. They have been sought through careful review and analysis of both theoretical and empirical literature by methods of textual research (Clingan, 2008) and constant comparative analysis (Glaser & Strauss, 1967). By way of textual research a methodological lens was defined to identify general themes, and by way of constant comparative analysis these themes were developed further through the analysis and classification of specific instances of those themes in the texts reviewed. Ten such principles were identified: repetition, time, step size, sequence, contrast, significance, feedback, context, engagement, and agency. These ten facilitative principles were then organized in the context of a comprehensive principles-of-learning framework, which includes the four additional principles of potential, target, change, and practice.

The introduction of e-learning made way for advancements in learning and technology with individuals being exposed to electronic learning and teaching environments. At first, the introduction of e-learning into the educational sphere was intended to simply enhance traditional teaching and learning; however, technology then took the lead as a tool to materially enhance the concept of e-learning in education. Inevitably, technology’s impact on learning drove the delivery of electronic educational content but it also caused widespread debate about best practice in the design of e-learning systems. Since then, the phenomenal influx of technology enhancements that has been created has led most learners into a digital education era that cannot now function without it. At first, e-learning systems were forced to adapt to change as a result of e-learning trends and as a symbolic move from traditional learning to more innovative methods of learning and teaching. As such, e-learning remained affected by pedagogy, technology and curriculum changes outside of a structured, guided framework. Varying definitions exist as a result of the diverse understanding of the contributions and role of pedagogy and technology toward e-learning. There is a misconception and confusion of elearning attributed to the lack of a formally accepted definition which would identify with the need for pedagogy principles and guide researchers to apply models and frameworks to implement and improve the provision of e-learning systems. Although the effects of technology on learning are conclusive, the current dilemma is the lack of effective alignment of the pedagogy principles to suitable technology – an issue which has now become detrimental to learning. This study explores the various interpretations of e-learning definitions that allude to the incorporation of learning, technology and knowledge gained during e-learning interventions. However, as the research revealed a lack of any cohesive e-learning definition, this motivated the creation of a specific definition derived particularly for this study. In considering the role of technology in the e-learning environment, similar themes began to emerge that needed to be addressed holistically through e-learning. One of these themes was a need to focus on the formulation of a structured approach and pedagogical framework for the design and development of e-learning systems. The findings of the research identified e-learning frameworks and models that were in use. The outcome of an e-learning system framework drew on the research of extant models and frameworks and investigated the critical elements, particularly that of pedagogy in an e-learning environment. The proposed pedagogical framework for elearning was evaluated by means of a survey of organisations that produce e-learning systems. The findings of the survey were analysed to assess the alignment and relevance of the dimensions and elements in the framework to the design and development of e-learning systems. The proposed pedagogical e-learning framework is intended to add value to the design and development of e-learning systems with the core focus on pedagogy. In years to come, current and existing technologies and tools may become outdated, yet learning opportunities continue to evolve based on pedagogy, technology and curriculum requirements. By harmonising the synergy between pedagogy and technology, a pedagogically aligned e-learning framework can resolve the lack of pedagogy in elearning system design and development. / Information Science / M.Sc. (Information Systems)

The introduction of e-learning made way for advancements in learning and technology with individuals being exposed to electronic learning and teaching environments. At first, the introduction of e-learning into the educational sphere was intended to simply enhance traditional teaching and learning; however, technology then took the lead as a tool to materially enhance the concept of e-learning in education. Inevitably, technology’s impact on learning drove the delivery of electronic educational content but it also caused widespread debate about best practice in the design of e-learning systems. Since then, the phenomenal influx of technology enhancements that has been created has led most learners into a digital education era that cannot now function without it. At first, e-learning systems were forced to adapt to change as a result of e-learning trends and as a symbolic move from traditional learning to more innovative methods of learning and teaching. As such, e-learning remained affected by pedagogy, technology and curriculum changes outside of a structured, guided framework. Varying definitions exist as a result of the diverse understanding of the contributions and role of pedagogy and technology toward e-learning. There is a misconception and confusion of elearning attributed to the lack of a formally accepted definition which would identify with the need for pedagogy principles and guide researchers to apply models and frameworks to implement and improve the provision of e-learning systems. Although the effects of technology on learning are conclusive, the current dilemma is the lack of effective alignment of the pedagogy principles to suitable technology – an issue which has now become detrimental to learning. This study explores the various interpretations of e-learning definitions that allude to the incorporation of learning, technology and knowledge gained during e-learning interventions. However, as the research revealed a lack of any cohesive e-learning definition, this motivated the creation of a specific definition derived particularly for this study. In considering the role of technology in the e-learning environment, similar themes began to emerge that needed to be addressed holistically through e-learning. One of these themes was a need to focus on the formulation of a structured approach and pedagogical framework for the design and development of e-learning systems. The findings of the research identified e-learning frameworks and models that were in use. The outcome of an e-learning system framework drew on the research of extant models and frameworks and investigated the critical elements, particularly that of pedagogy in an e-learning environment. The proposed pedagogical framework for elearning was evaluated by means of a survey of organisations that produce e-learning systems. The findings of the survey were analysed to assess the alignment and relevance of the dimensions and elements in the framework to the design and development of e-learning systems. The proposed pedagogical e-learning framework is intended to add value to the design and development of e-learning systems with the core focus on pedagogy. In years to come, current and existing technologies and tools may become outdated, yet learning opportunities continue to evolve based on pedagogy, technology and curriculum requirements. By harmonising the synergy between pedagogy and technology, a pedagogically aligned e-learning framework can resolve the lack of pedagogy in elearning system design and development. / Information Science / M.Sc. (Information Systems)

Autism Spectrum Disorder (ASD) is part of the developmental disabilities. There are numerous symptoms for ASD patients, including lack of abilities in social interaction, communication obstacle and repeatable behaviors. Meanwhile, the rate of ASD prevalence has kept rising by the past 20 years from 1 out of 150 in 2000 to 1 out of 54 in 2016. In addition, the ASD population is quite large. Specifically, 3.5 million Americans live with ASD in the year of 2014, which will cost U.S. citizens $236-$262 billion dollars annually for autism services. So, it is critical to make an accurate diagnosis for preschool age children with ASD, in order to give them a better life. Instead of using traditional ASD behavioral tests, such as ADI-R, ADOS, and DSM-IV, we applied brain MRI images as input to make diagnosis. We revised 3D-ResNet structure to fit 110 preschool children's brain MRI data, along with Convolution 3D and VGG model. The prediction accuracy with raw data is 65.22%. The accuracy is significantly improved to 82.61% by removing the noise around the brain. We also showed the speed of ML prediction is 308 times faster than behavior tests.

The field of influencer marketing has experienced rapid growth in recent years. However, uncovering the true effectiveness of this marketing approach remains a significant challenge. This thesis addresses the challenge of predicting the effectiveness of influencer marketing campaigns by employing advanced machine learning techniques, specifically the Auto Machine Learning framework Autogluon. With the aim of democratizing machine learning and empowering businesses in the influencer marketing domain, this work leverages Autogluon to predict the interactions generated by influencers when posting affiliate links. By evaluating various settings of AutoGluon and assessing the performance using metrics such as R-squared score, we observed promising results with good predictive accuracy. The findings from our study contribute to critical discussions in the field. This research offers a streamlined and efficient approach to machine learning, reducing the need for extensive manual model tuning and enabling marketers to make informed decisions and optimize their campaign strategies. The outcomes of this study have practical implications for businesses, allowing them to effectively predict campaign interactions and maximize the impact of influencer marketing initiatives. By leveraging the power of automated machine learning, this thesis opens up new opportunities for businesses to harness the potential of influencer marketing in driving successful marketing campaigns. / Influencer marketing trenden har ökat markant de senaste aren men effektiviteten av denna marknadsföringsmetod är till stor del oviss. Denna avhandling utfårskar svårigheten med att förutse effekten av influencer marketing kampanjer med hjälp av avancerad maskininlärningsteknik, specifikt Auto Machine Learning-ramverket Autogluon. Med målet att demokratiserar och uppmuntra företag att använda maskininlärning, utforskar denna avhandling Autogluon för att förutse interageringar som genereras när influerare publicerar affiliate länkar. Genom att utvärdera olika inställningar av Autogluon och analysera olika data som till exempel R-kvadratvärde observerade vi lovande resultat med god förutsägbar precision. Resultaten från vår studie bidrar till kritiska diskussioner inom området. Denna forskning erbjuder en strömlinjeformad och effektiv metod för maskininlärning, vilket minskar behovet av omfattande manuellt modellarbete och möjliggör för marknadsförare att fatta informerade beslut och optimera sina kampanjstrategier. Resultaten av denna studie har praktiska implikationer för företag, vilket gör det möjligt för dem att effektivt förutse interaktioner i kampanjer och maximera effekten av influencer marketingvertyg. Genom att applicera automatiserad maskininlärning öppnar denna avhandling nya möjligheter för företag att dra nytta av potentialen hos influencer marketing för att driva framgångsrika marknadsföringskampanjer.

The purpose of the study has been to investigate and shed light on practical measures companies take to create a culture that promotes learning, as well as the role of technology. It is an important topic for organizations to face major challenges regarding reskilling and upskilling of employees, to ensure that the company has the right skills for the future. We have examined 11 companies where we took a closer look at their organizational structure, how they use leadership around learning, their vision, mission and strategy for learning, what technology is used for learning (and how and why exactly these technologies), how they create and buy digital content / courses, what can be measured and used as guidelines for driving learning and finally we have looked at the challenges production companies are especially faced with. Our analysis shows that there are some common denominators in which competencies and tasks must exist and take place internally to be able to facilitate work towards a learning culture, that learning is designed after having a high business relevance, that the top management's attitude to learning is essential, that learning technologies are used frequently, there is data on learning activities that can be used as guidelines and that production companies need to take special measures to be able to include their entire workforce in their learning initiatives. Our analysis also shows that the quality and usefulness of learning technologies has accelerated in recent years and has been given a leading role in organizations' investments to improve the learning culture. In the report, we propose that companies realize the power they have to influence how learning is done by setting up and working with the essential building blocks of the learning ecosystem we have identified. / Syftet med studien har varit att undersöka och belysa praktiska åtgärder företag tar sig an för att skapa en kultur som främjar lärande, samt vilken roll teknologi har. Det är ett viktigt ämne för att organisationer står inför stora utmaningar gällande upplärning och omskolning av anställda, för att säkerställa att företaget har rätt kompetenser. Vi har undersökt 11 företag där vi har tittat närmare på deras organisationsstruktur, hur de använder sig av ledarskap kring lärande, deras vision, mission och strategi för lärande, vilka teknologier som används för lärande (samt hur och varför just dessa teknologier), hur de skapar och köper in digitalt innehåll/kurser, vad som kan mätas och användas som riktlinjer för att driva lärande och till sist har vi tittat på utmaningar produktionsföretag speciellt ställs inför. Vår analys visar att det finns några gemensamma nämnare i vilka kompetenser och arbetsuppgifter som ska finnas internt för att lättare kunna arbeta mot en lärande kultur, att lärande designas efter att ha hög affärsrelevans, att högsta ledningens inställning till lärande är essentiell, att lärande teknologier används flitigt, det finns data kring lärande aktiviteter som kan användas som riktlinjer samt att produktionsbolag behöver vidta särskilda åtgärder för att kunna inkludera hela sin arbetsstyrka i sina lärande initiativ. Vår analys visar även att kvaliteten på och nyttan av lärande teknologier har accelererat de senaste åren och har fått en huvudroll i organisationers investeringar för att förbättra lärande kulturen. I rapporten föreslår vi att företag inser makten de har att påverka hur lärande går till genom att sätta upp och arbeta med de olika delarna vi belyser är essentiella i ett lärande ekosystem.

This thesis examines the possibilities of linking historiographical education and drama curriculum in primary school using action research. The theoretical part examines various educational and psychological bases that support the idea of linking drama and historiographical education and defines the possibilities of the involvement of drama as a teaching method in the primary school. The practical part contains specific proposal of two lessons with historiographical themes and also includes evaluation of their implementation in 4th and 5th class. Both lessons are designed and implemented in accordance with the teachings of Three-phase, respecting the psychological aspects of the target group. Lessons use mainly drama methods, marginally methods of curriculum Reading and writing to critical thinking, Experiential learning, Project teaching and Cooperative learning are used. Action research is evaluated through observation and detailed description of teacher reflection.

<p>Over the past decade, distributed representation learning has emerged as a popular alternative to conventional centralized machine learning training. The increasing interest in distributed representation learning, specifically federated learning, can be attributed to its fundamental property that promotes data privacy and communication savings. While conventional ML encourages aggregating data at a central location (e.g., data centers), distributed representation learning advocates keeping data at the source and instead transmitting model parameters across the network. However, since the advent of deep learning, model sizes have become increasingly large often comprising million-billions of parameters, which leads to the problem of communication latency in the learning process. In this thesis, we propose to tackle the problem of communication latency in two different ways: (i) learning private representation of data to enable its sharing, and (ii) reducing the communication latency by minimizing the corresponding long-range communication requirements.</p> <p><br></p> <p>To tackle the former goal, we first start by studying the problem of learning representations that are private yet informative, i.e., providing information about intended ''ally'' targets while hiding sensitive ''adversary'' attributes. We propose Exclusion-Inclusion Generative Adversarial Network (EIGAN), a generalized private representation learning (PRL) architecture that accounts for multiple ally and adversary attributes, unlike existing PRL solutions. We then address the practical constraints of the distributed datasets by developing Distributed EIGAN (D-EIGAN), the first distributed PRL method that learns a private representation at each node without transmitting the source data. We theoretically analyze the behavior of adversaries under the optimal EIGAN and D-EIGAN encoders and the impact of dependencies among ally and adversary tasks on the optimization objective. Our experiments on various datasets demonstrate the advantages of EIGAN in terms of performance, robustness, and scalability. In particular, EIGAN outperforms the previous state-of-the-art by a significant accuracy margin (47% improvement), and D-EIGAN's performance is consistently on par with EIGAN under different network settings.</p> <p><br></p> <p>We next tackle the latter objective - reducing the communication latency - and propose two timescale hybrid federated learning (TT-HF), a semi-decentralized learning architecture that combines the conventional device-to-server communication paradigm for federated learning with device-to-device (D2D) communications for model training. In TT-HF, during each global aggregation interval, devices (i) perform multiple stochastic gradient descent iterations on their individual datasets, and (ii) aperiodically engage in consensus procedure of their model parameters through cooperative, distributed D2D communications within local clusters. With a new general definition of gradient diversity, we formally study the convergence behavior of TT-HF, resulting in new convergence bounds for distributed ML. We leverage our convergence bounds to develop an adaptive control algorithm that tunes the step size, D2D communication rounds, and global aggregation period of TT-HF over time to target a sublinear convergence rate of O(1/t) while minimizing network resource utilization. Our subsequent experiments demonstrate that TT-HF significantly outperforms the current art in federated learning in terms of model accuracy and/or network energy consumption in different scenarios where local device datasets exhibit statistical heterogeneity. Finally, our numerical evaluations demonstrate robustness against outages caused by fading channels, as well favorable performance with non-convex loss functions.</p>

In TVET colleges, the traditional face-to-face mode of knowledge delivery appears to be the norm. Knowledge is often shared in a teaching space during a particular period of time. Students and a lecturer need to be in a specified venue during an allocated time slot for the learning process to take place which includes obtaining knowledge from the lecturer, sharing views and storing knowledge in their minds. There is often no interaction with the lecturer beyond the classroom. As such, learners with learning difficulties have no alternative platform into which they can get support; which compromises the quality of education and students’ success rate. The use of e-learning permits students to finalise a course in their own time and at their own location. It also implies that students are at an advantage as they do not need to go to a particular learning institution, and they can proceed with the training at their own pace. This research investigated how e-learning may be used as an enabler of learning by overcoming barriers associated with face-to-face learning. This was achieved through the development of a proposed e-learning framework based on the existing literature. The proposed framework was then tested through a survey distributed among TVET stakeholders to offer an improved framework. Furthermore, the improved framework was used to develop an e-learning architecture and prototype which can help guide institutions who wish to adopt e-learning. / Information Technology / M. Tech. (Information Technology)

The diploma thesis deals with interdisciplinary teaching and learning approaches at the level of a planned curriculum. The theoretical part is devoted to the issues of interdisciplinary teaching and learning approaches, description of school-age children and game-based learning. It includes the concepts of integration in teaching, numeracy, instructor, learning, motivation and game-based learning. There is also mentioned the Framework Educational Program for Primary Education, key competencies and its selected educational areas. The practical part contains a set of activities that integrate interdisciplinary teaching and learning. For each activity there is a description of its realization from the point of view of the author of the diploma thesis.