Engineering Education experiences turbulent changes, both from government pressures and from industry demands on readdressing the requirements of graduate capability. Despite vast amounts of engineering literature discussing ‘change’ within the field, engineering curricula still maintains its predominant pedagogic model of dissemination to students as it did in previous decades. Technology Enhanced Learning in education has created new and flexible options in the delivery and assessment of teaching and learning, but uptake is limited and approached with caution within Engineering Education. This mixed methods research introduces an inclusive and innovative approach to Engineering Education assessment techniques utilising an integrated blended learning strategy to the implementation of Technology Enhanced Learning within engineering curriculums. The research explores and assesses the effectiveness of Technology Enhanced Learning and educational pedagogies within Engineering Education frameworks to enhance and develop student learning, digital literacy and employability. Preliminary research positioned the research, utilising observation and interview techniques to baseline current pedagogic practices in undergraduate Engineering Education against current literature. An alternative method of video assessment was implemented and embedded following a two year cycle of action research within a cohort of two undergraduate engineering modules. A prototype ‘toolkit’ was created using Xerte Online Toolkits (XOT) to facilitate student learning and support for the assessment. Additional techniques inside the cycles gained further qualitative and quantitative data via a survey and focus groups. Student learning and assessment results showed significant improvement following the introduction of this approach and validated the transferability of this technique into other educational disciplines. An industry based survey validated chosen research methods and provided a comparison of viewpoints on key issues surrounding Engineering Education against existing stakeholders. The research introduces a new innovative approach to Engineering Education utilising Technology Enhanced Learning, validated through positive industry feedback and student academic achievement and satisfaction. Significant improvements on student employability and engineering ‘soft skills’ are evidenced.

Although a mandate was given in an urban southern university for instructors in the Adult Professional Studies Program (APS) to begin transitioning their face-to-face courses to online curricula, few courses have been converted. The purpose of this case study was to determine APS instructors' perceptions of developing and transitioning face-to-face courses to an online format. Lewin's change theory and force field analysis provided the conceptual framework for this study. The research questions concerned the faculty's perceptions of developing and transitioning courses to an online format. A purposeful sample of fulltime and adjunct faculty, with different levels of expertise in online courses within the APS department was invited to participate. Semistructured interview data from these faculty (n = 9) - were analyzed manually using color coding to determine the needs and barriers for instructors transitioning their face-to-face courses to online curricula. According to the study findings, the APS faculty saw value in online education, but perceived many obstacles that keep them from fully investing into this type of instruction. 10 themes were identified through data analysis in this study. These themes were used to create a 3-day professional development (PD) project for faculty members in the APS to assist educators in creating appropriate innovations for teaching and learning in an online setting. Creating a comprehensive, 3-day PD training for APS staff and faculty that address barriers noted in the findings of the study and diverse learning opportunities created learning opportunities for nontraditional students in the APS.

Technology evolution throughout history has initiated many changes in different aspects of human activities. Learning, as one of the most representative human activities has also been subject to these changes. Nowadays, the use of information and communication technologies has considerably changed the way people learn and collaborate. These changes have been accompanied by new approaches to support learning using a wide range of mobile devices, software applications and different communication platforms. In these technology rich landscapes, the notion of context emerges as a crucial component to be considered for the design and technical implementation of technology-enhanced learning environments. The main research question investigated in this thesis relates to the use of different context instantiations for the design and development of innovative technology-enhanced learning environments.This thesis is a collection of eight papers that describe the results of the research efforts conducted in four different experimental cases during a period of four years. These experiments have been designed and developed as part of two research projects. The theoretical foundations that guided this research were based on the view of context and interaction from a learning theory, human-computer-interaction perspective, as well as dimensional data modelling techniques. Different methodological approaches, (such as action-oriented, design-based research and case study) have been used while investigating the main research question. The main contribution that this thesis offers to the research community is a conceptual context model accompanied by a dimensional data model that can be used as a design tool for embedding learning activities in context. In the four trials that encompass my empirical work, the conceptual model proposed in the thesis guided the design and technical development of the different novel technology-enhanced learning activities. The outcomes of these efforts provided various insights regarding the use of different context instantiations that have implications for the design and development of these environments. This thesis advocates that computational context attributes should be used as metadata descriptors that would potentially promote personalization and interoperability of digital learning content. Content personalization offers opportunities for personalized learning that increases learners’ engagement and eventually could lead to better learning results. Furthermore, the research and industrial community could use the context model developed in this thesis as a guiding tool to promote the creation of new ways to personalize services and technologies.

The design of intelligent learning environments requires significant up-front resources and expertise. These environments generally maintain complex and comprehensive knowledge bases describing pedagogical approaches, learner traits, and content models. This has limited the influence of these technologies in higher education, which instead largely uses learning content management systems in order to deliver non-classroom instruction to learners. This dissertation puts forth a data-assisted approach to embedding intelligence within learning environments. In this approach, instructional experts are provided with summaries of the activities of learners who interact with technology enhanced learning tools. These experts, which may include instructors, instructional designers, educational technologists, and others, use this data to gain insight into the activities of their learners. These insights lead experts to form instructional interventions which can be used to enhance the learning experience. The novel aspect of this approach is that the actions of the intelligent learning environment are now not just those of the learners and software constructs, but also those of the educational experts who may be supporting the learning process. The kinds of insights and interventions that come from application of the data-assisted approach vary with the domain being taught, the epistemology and pedagogical techniques being employed, and the particulars of the cohort being instructed. In this dissertation, three investigations using the data-assisted approach are described. The first of these demonstrates the effects of making available to instructors novel sociogram-based visualizations of online asynchronous discourse. By making instructors aware of the discussion habits of both themselves and learners, the instructors are better able to measure the effect of their teaching practice. This enables them to change their activities in response to the social networks that form between their learners, allowing them to react to deficiencies in the learning environment. Through these visualizations it is demonstrated that instructors can effectively change their pedagogy based on seeing data of their students’ interactions. The second investigation described in this dissertation is the application of unsupervised machine learning to the viewing habits of learners using lecture capture facilities. By clustering learners into groups based on behaviour and correlating groups with academic outcome, a model of positive learning activity can be described. This is particularly useful for instructional designers who are evaluating the role of learning technologies in programs as it contextualizes how technologies enable success in learners. Through this investigation it is demonstrated that the viewership data of learners can be used to assist designers in building higher level models of learning that can be used for evaluating the use of specific tools in blended learning situations. Finally, the results of applying supervised machine learning to the indexing of lecture video is described. Usage data collected from software is increasingly being used by software engineers to make technologies that are more customizable and adaptable. In this dissertation, it is demonstrated that supervised machine learning can provide human-like indexing of lecture videos that is more accurate than current techniques. Further, these indices can be customized for groups of learners, increasing the level of personalization in the learning environment. This investigation demonstrates that the data-assisted approach can also be used by application developers who are building software features for personalization into intelligent learning environments. Through this work, it is shown that a data-assisted approach to supporting instructional interventions in technology enhanced learning environments is both possible and can positively impact the teaching and learning process. By making available to instructional experts the online activities of learners, experts can better understand and react to patterns of use that develop, making for a more effective and personalized learning environment. This approach differs from traditional methods of building intelligent learning environments, which apply learning theories a priori to instructional design, and do not leverage the in situ data collected about learners.

<p>Learning materials have multiple forms, such as books, overhead slides, computer files, blackboard notes by teachers, narration to the notes, video/audio tapes etc. Since the forms are highly inhomogeneous, it becomes difficult to collect and practically use them by a particular learner for individual study at home. Such multiple media are also expensive in management, since human resources are needed to keep the material repositories in order. One solution of the problem lies in centralized active digital repositories. Such repositories aim to simplify the learner’s work and boost learning efficiency. With introduction of interactivity and live communication tools such repositories become learning platforms exceeding the functionality of “passive” digital libraries. Such learning platforms could be easily used both for on-campus and distance education.</p><p>This dissertation presents an evaluation of a digital repository of interactive multimedia content in the field of Heat and Power Technology: Computerized Educational Platform (CompEdu HPT). The platform evaluation consisted of integration of the tool into the university curriculum and then collection of feedback from students and teachers. The evaluation concerned usefulness of the platform for learning, aspects of instruction improvement, collecting observations about how the platform is used by students, as well as their opinions about the IT application direction chosen. The methods included: online feedback forms, questionnaires, interviews, discussions and observations.</p><p>The evaluation demonstrated that the main strength of the platform is the integration of learning materials in one portable package. The students appreciated structured and logically arranged information that was available for easy access. Coverage of a broad area of knowledge related to heat and power technology was also pointed out as an advantage with reflection on the very low price of acquisition of the materials. The most popular elements of the content in use included: simulations, lecture notes, the print function, the glossary, and calculation exercises. A major part of the students declared the high value of CompEdu in facilitating home study. Nevertheless, not all the students had a positive impression: around one-fifth of them did not find the platform useful and expressed preference for more traditional learning media. The majority of the negative opinions concerned content quality, which directly related to weaknesses of the content production and review process.</p><p>The evaluation emphasized the importance of material quality and amount as the key issue for a good learning platform with relatively smaller importance of presentation forms. The evaluation also considered aspects of functionality from the user point of view. Differentiation between popularity of simulations showed that simulations used by teachers during lectures have higher educational value than those for individual use only. The popularity of the printing option indicated a need for adaptation of digital materials for paper publishing. The general conclusion for practical use of multimedia tools in education was that high usability and simplicity of information access should be the focus point of any chosen approach in the direction.</p><p>The CompEdu evaluation suggested that after thorough content review and addition of an efficient search mechanism the platform can successfully deliver rich learning content. The platform gave an extensive real-case illustration of how multimedia can be used in educational practice. Due to the evaluation, the CompEdu e-learning group has collected rich experience and know-how in the field of active knowledge repositories. The experience will be used for development of a more sophisticated learning platform working in the global Internet environment with major focus on information accessibility by easy search.</p>

In traditional models of university education, students gather in classrooms, listen to instructors lecture on specific topics, and take notes with limited time for interaction. Students are then expected to spend additional time outside of the classroom reading textbooks, completing assignments, and preparing for tests. Instructors are viewed as experts providing information to students in much the same manner that they learned the content as students in college. The advent of the World Wide Web in 1991 allowed a dramatic change in the way students and faculty gather information, conduct research, and publish ideas. Internet-based technologies can transform traditional classroom experiences. Student participation can be increased by promoting group and collaborative learning online, and by the use of tools such as e-mail, discussion boards, and synchronous chat sessions. The objectives of this study were to 1) determine which factors affected faculty members’ use of technology integration in their instruction, and 2) determine what effect the integration of technology had on the role and teaching styles of faculty members. The study employed a mixed-methods research methodology. A survey instrument was developed and sent to faculty members at the five largest, public research institutions. The level of technology integration was calculated on a scale ranging from nonuse to full integration. The scale included practices such as providing online discussion areas, allowing/requiring students to use the Internet for assignments, and using anonymous online surveys to gather student feedback. Faculty members were then asked to elaborate on their answers. After the quantitative and qualitative survey results were analyzed, a select group of faculty members at one campus were interviewed to verify or dispute the findings. The survey results revealed the factors that significantly contributed to the overall level of technology integration were: instructional resources, professional and personal computer use, level of class, gender, title, and type of online teaching experience. One of the most significant factors was the level of instructional resources. Instructors with a facilitative teaching style were most likely to integrate technology into their instruction. This information can inform institutions when creating faculty development programs and budgeting limited resources. / text

The ability to carry communication services around, combined with the ubiquitous presence of computing technology, affects everything we do from how we pay for things to how we expect to interact with public institutions such as schools. There are now plenty of systems that convey education by utilizing mobile devices. As an extension of technology moving towards ubiquity, there are efforts aiming to bring this to an educational use as well. Efforts in this direction are channelized in the field of mobile learning. The speed of technological development, and the possibilities it brings introduces a large number of challenges when implemented in educational settings. These challenges can be related to for example pedagogical aspects, tools, implementations and organizations. Recent developments including the notions of learning ecosystems, learning landscapes and organizations suggest that the domain of mobile learning can be negatively affected from the lack of a systematic reuse approach. This thesis pursues these challenges by investigating how systematic reuse can be promoted in mobile learning systems. A collection of five peer-reviewed publications that elaborates on the different stages of the research process pursuing the main research question forms the core of this thesis. This research process includes a survey stage, elaborating on different aspects related to reuse and mobile learning, an analysis stage that resulted in a descriptive model and several additional domain models; and finally a stage where the descriptive model is refined into a reference model for mobile learning ecosystems. The outcomes of these activities and the analysis of these results provide some fundamental building blocks regarding how to approach the challenge of reuse in mobile learning systems. The proposed reference model can be considered as the first step towards the creation of a common vocabulary that can be used to compare Software Ecosystems within the domain of mobile learning.

This paper provides a report on the experimental collaborative and distributed development of a prototypic Widget-based PLE. The development process is described and detailed taking into account the requirements of a language learning scenario. First results are presented, and developer experiences are discussed critically with a focus on the development process as well as problems with current Widget technologies and interoperability.

yes

Recently, there has been an increasing shift in education, where various digital technologies are applied to a greater extent. One of the emerging educational technologies is artificial intelligence (AI) technology, which is often argued to have the potential to reshape the traditional educational landscape through for example intelligent guidance and assessment systems, as well as personal learning environments. An article in Artificial Intelligence Review states that the education sector at universities is increasingly characterized by AI used by teachers and students, consisting of intelligent tutoring systems, teaching robots, and adaptive learning systems. Trust - which is considered the cornerstone of humanity's relationship with AI - is essential to this transformation. There is a considerable knowledge gap regarding how teachers experience trust in AI-based education technology, within higher education. Therefore, this exploratory case study aims to examine teachers' trust in AI, and more specifically within the context of Singaporean higher education. This study is based on an online survey where eight teachers participated. Although that is a low count of participants, the study explores the perceived trust in, and benefits of AI in an academic environment. Furthermore, where there is a lack of trust in AI diagnosis, it is due to the fact that today's AI technology often consists of black-box models that lack transparency of the system's internal functions work. Finally, concerning how teachers work alongside AI to improve pedagogy, the study concludes that implementing AI-based technology in higher education will never replace the traditional education system in terms of social interaction. / Nyligen har det skett ett skifte inom utbildning där olika digitala teknologier tillämpas i allt större utsträckning. En av dessa teknologier är artificiell intelligens (AI), som ofta hävdas kunna omforma det traditionella utbildningslandskapet genom personliga inlärningsmiljöer och intelligenta väglednings- och bedömningssystem. En artikel i Artificial Intelligence Review beskriver att dagens utbildningssektor vid universitet kännetecknas alltmer av AI som används av både lärare och studenter, där system bestående av intelligenta handledningssystem, undervisningsrobotar och adaptiva lärsystem används. För dessa anses förtroende vara hörnstenen i människans relation till AI - som är avgörande för att denna transformation av utbildningen ska fungera. Det finns en avsevärd kunskapslucka kring det förtroende lärare inom högre utbildning har för AI-baserad utbildningsteknik. Därför syftar denna explorativa fallstudie till att undersöka lärares förtroende för AI, och mer specifikt inom ramen för högre utbildning i Singapore. Denna studie är bygger på en webbenkät där åtta lärare deltog. Även om det är ett lågt antal deltagare, utforskar studien det upplevda förtroendet för AI, samt fördelarna med att använda det i en akademisk miljö. Vidare, där det saknas förtroende för AI-diagnostik, beror det på att dagens AI-teknik ofta består av black-box-modeller som saknar transparens i systemets interna funktioners arbete. Slutligen, när det gäller hur lärare arbetar tillsammans med AI för att förbättra pedagogiken, drar studien slutsatsen att implementering av AI-baserad teknik i högre utbildning aldrig kommer att ersätta det traditionella utbildningssystemet när det gäller social interaktion.