Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

Standardising the design of educational computer reading programs for children.

Educationalists working in the sphere of special education, psychologists and software engineers continue to debate the efficacy of technology interfaces and the merits of information technology with regard to supporting learning in children with Autistic Spectrum Disorder (ASD), and the need to standardise software design for this group. This research argues that, for these children to optimise the use of this technology, it must be designed to meet the learning needs and characteristics of this condition, and so a design/development standard is needed. There is currently no instruction to aid educational professionals in choosing suitable computer programs that can be employed to support learning to read in children with ASD. The present research offers a rigorous comparative analysis of the multimedia conditions. A selection instruction (SI) was developed to facilitate the choice of appropriate computer programs for children with ASD, and forms part of the pilot study for this investigation, which was later modified and developed into an educational computer programs design standard. This SI serves as a set of guidelines that is intended to assist professionals and the parents/guardians of children with ASD in their search for good, useable programs that will assist in the acquisition of early reading skills by this group. This research advocates the development of effective computer programs based on individualistic considerations and the stringent application of Human Computer Interaction (HCI) principles in the design of multimedia computer technology for children with ASD. Two educational programs were employed in the investigation, and the data collection method included quantitative (pre-tests; a comparative study of children with ASD and typically developing children in videorecorded sessions, and post-tests) and qualitative (interviews, and an attitude questionnaire) methods. This approach was triangulated, thereby promoting the validity and rigour of the investigation. The present research concludes that, although there were recorded gains in the application of computer technology to teach new words to children with ASD, there were problems relating to the appropriateness and suitability of the programs for the children employed in this research, as detected during the interviews and from the attitude questionnaires, noting the need for autistic preferences in the design and development of these educational computer programs. This investigation offers a broader approach to the theoretical understanding and explanation of autistic learning styles, reading methodologies and issues relating to the design, development and usability of multimedia computer technology. Attention is drawn to the inadequacy of the existing technology and research into ASD and how the disorder affects learning in these children

Designing intelligent support for learning from and in everyday contexts

Motivation and engagement in learning benefit from a good match of learning settings and materials to individual learner contexts. This includes intrinsic context factors such as prior knowledge and personal interests but also extrinsic factors such as the current environment. Recent developments in adaptive and intelligent technology enable the personalisation of context-aware learning. For example, computer vision algorithms, machine translation, and Augmented Reality make it possible to support the creation of meaningful connections between learners and their context. However, for successful adoption in everyday life, these technologies also need to consider the learner experience. This thesis investigates the design of personalised context-aware learning experiences through the lens of ubiquitous and self-directed language learning as a multi-faceted learning domain. Specifically, it presents and discusses the design, implementation, and evaluation of technology support for learning in and from learners’ everyday contexts with a strong focus on the learner perspective and user experience. The work is guided by four different roles that technology can take on in context-aware ubiquitous learning: For enhancing learning situations, it can (1) sense and (2) trigger in learners’ everyday contexts. For enhancing learning contents, it can (3) augment activities and (4) generate learning material from learner everyday contexts. With regards to the sensing role, the thesis investigates how learners typically use mobile learning apps in everyday contexts. Activity and context logging, combined with experience sampling, confirm that mobile learning sessions spread across the day and occur in different settings. However, they are typically short and frequently interrupted. This indicates that learners may benefit from better integrating learning into everyday contexts, e.g. by supporting task resumption. Subsequently, we explore how this integration could be supported with intelligent triggers linked to opportune moments for learning. We conceptualise and evaluate different trigger types based on interaction patterns and context detection. Our findings show that simple interactions (e.g. plugging in headphones) are promising for capturing both availability and willingness to engage in a learning activity. We discuss how similar interaction triggers could be adapted to match individual habits. In the area of enhancing learning contents, we first investigate how enjoyable everyday activities could be augmented for learning without disrupting these activities. Specifically, we assess the learner experience with interactive grammar support in e-readers and adapted captions for audio-visual media. Participants in our studies felt that the learning augmentations successfully supported their learning process. The information load of the learning support should match the learners’ current needs to maintain the activity flow. Learners may need encouragement to opt for novel concepts optimised for learning (e.g. time-synchronised captions) rather than sticking to habits (e.g. standard captions). Next, the thesis explores learner needs and preferences in generating their own personalised learning material from their context. We design and evaluate automated content generation methods that generate learning opportunities from objects in the learner’s environment. The connection to the learner’s context is established with state-of-the-art technology, such as object detection and Augmented Reality. Through several user studies, we show that learning performance and engagement with auto-generated personalised learning material is comparable to predefined and manually generated content. Findings further indicate that the success of personalisation depends on the effort required to generate content and whether the generation results match the learner’s expectations. Through the different perspectives examined in this thesis, we provide new insights into challenges and opportunities that we synthesise in a framework for context-aware ubiquitous learning technology. The findings also have more general implications for the interaction design of personalised and context-aware intelligent systems. Notably, for the auto-generation of personalised content, it is essential to consider not only correctness from a technological perspective but also how users may perceive the results.Lernmotivation und Engagement profitieren davon, wenn Lernumgebungen und Lernmaterialien auf den individuellen Kontext der Lernenden abgestimmt sind. Dieser umfasst sowohl intrinsische Faktoren wie Vorkenntnisse und persönliche Interessen, aber auch extrinsische Faktoren wie die aktuelle Umgebung. Aktuelle Weiterentwicklungen im Bereich adaptiver und intelligenter Technologien ermöglichen es, Lernen kontextbewusst zu personalisieren. So können mithilfe von Computer-Vision-Algorithmen, maschineller Übersetzung und Augmented Reality sinnvolle Verknüpfungen zwischen Lernenden und ihrem Kontext geschaffen werden. Allerdings müssen diese Technologien für einen erfolgreichen Einsatz im Alltag auch die Lernerfahrung mit einbeziehen. Diese Arbeit untersucht die Gestaltung personalisierter kontextbewusster Lernerfahrungen aus der Perspektive des ubiquitären und self-directed Learning im Sprachenlernen, einem vielseitigen Lernbereich. Insbesondere wird die Konzeption, Implementierung und Evaluierung von Technologieunterstützung für das Sprachenlernen in und aus dem Alltagskontext der Lernenden vorgestellt und diskutiert, wobei der Schwerpunkt auf der Perspektive der Lernenden und der Nutzererfahrung liegt. Die Arbeit orientiert sich an vier verschiedenen Rollen, die Technologie im kontextbewussten Lernen einnehmen kann. Um Lernsituationen anzureichern, kann Technologie im Alltagskontext von Lernenden (1) erfassen und (2) auslösen. Um Lerninhalte anzureichern, kann Technologie aus dem Alltagskontext (3) Aktivitäten augmentieren und (4) Inhalte generieren. Im Hinblick auf die erfassende Rolle von Technologie wird in dieser Arbeit untersucht, wie die Lernenden mobile Lern-Apps in alltäglichen Kontexten nutzen. Die Aufzeichnung von Aktivitäten und Kontexten in Kombination mit Experience Sampling bestätigt, dass Lerneinheiten im mobilen Lernen über den Tag verteilt sind und in verschiedenen Umgebungen stattfinden. Allerdings sind sie in der Regel kurz und werden häufig unterbrochen. Dies deutet darauf hin, dass die Lernenden von einer besseren Integration des Lernens in ihren Alltagskontext profitieren könnten, z. B. durch Unterstützung des Wiedereinstiegs nach einer Unterbrechung. Anschließend untersuchen wir, wie diese Integration durch intelligente Trigger unterstützt werden könnte, die mit passenden Lernzeitpunkten verknüpft sind. Wir konzipieren und evaluieren verschiedene Arten von Triggern auf Basis von Interaktionsmustern und Kontexterkennung. Unsere Ergebnisse zeigen, dass einfache Interaktionen (z. B. das Einstecken von Kopfhörern) vielversprechend dafür sind, sowohl die Verfügbarkeit als auch die Bereitschaft für eine Lernaktivität zu erfassen. Wir diskutieren, wie ähnliche Interaktionstrigger an individuelle Gewohnheiten angepasst werden können. Im Bereich der Augmentierung von Lerninhalten untersuchen wir zunächst, wie unterhaltsame Alltagsaktivitäten für das Lernen aufbereitet werden können, ohne diese Aktivitäten zu beeinträchtigen. Konkret bewerten wir die Lernerfahrung mit interaktiver Grammatikunterstützung in E-Readern und angepassten Untertiteln für audiovisuelle Medien. Die Teilnehmer:innen unserer Studien fanden, dass die Lernunterstützung ihren Lernprozess erfolgreich förderte. Die Informationslast im Lernsystem sollte auf die aktuellen Bedürfnisse der Lernenden angepasst werden, damit das Flow-Erlebnis nicht beeinträchtigt wird. Die Lernenden brauchen möglicherweise Ermutigung dafür, sich für neuartige, lernoptimierte Konzepte zu entscheiden (z. B. zeitsynchrone Untertitel), anstatt an Gewohnheiten festzuhalten (z. B. Standarduntertitel). Als Nächstes werden in dieser Arbeit die Bedürfnisse und Präferenzen der Lernenden bei der Erstellung ihres eigenen personalisierten Lernmaterials aus ihrem Kontext untersucht. Insbesondere werden Methoden zur automatischen Generierung von Inhalten entwickelt und evaluiert, die Lernmöglichkeiten aus Objekten in der Umgebung des Lernenden generieren. Die Verbindung zum Kontext des Lernenden wird durch aktuelle Technologien wie Objekterkennung und Augmented Reality hergestellt. Wir zeigen anhand mehrerer Nutzerstudien, dass die Lernleistung und das Engagement bei automatisch personalisiertem Lernmaterial mit vordefinierten und manuell erstellten Inhalten vergleichbar sind. Die Ergebnisse zeigen außerdem, dass der Erfolg der Personalisierung vom Aufwand abhängt, der für die Erstellung der Inhalte erforderlich ist, und davon, ob die generierten Materialien den Erwartungen der Lernenden entsprechen. Die verschiedenen Perspektiven, die in dieser Arbeit untersucht werden, bieten neue Einblicke in Herausforderungen und Möglichkeiten, die wir in einem Framework für kontextbewusste ubiquitäre Lerntechnologie zusammenfassen. Die Ergebnisse haben auch allgemeinere Auswirkungen auf die Gestaltung der Interaktion mit personalisierten und kontextbewussten intelligenten Systemen. Beispielsweise ist es bei der automatischen Generierung personalisierter Inhalte wichtig, nicht nur die Korrektheit aus technologischer Sicht zu berücksichtigen, sondern auch, wie die Nutzer die Ergebnisse wahrnehmen

Human-machine communication for educational systems design

This book contains the papers presented at the NATO Advanced Study Institute (ASI) on the Basics of man-machine communication for the design of educational systems, held August 16-26, 1993, in Eindhoven, The Netherland

Effects of color and animation on visual short -term memory in computer-environment learning tasks

The goals of this research study were to gain a better understanding of the effects of color and animation on visual short-term memory (STM) in computer-environment learning tasks. The research methodology was based on an investigative design that attempted to address weaknesses of previous visual STM research (Klauer & Zhao, 2004) to provide information readily applicable to instructional design and technology. A 3 x 2 x 3 totally-within participants, repeated-measures Factorial Analysis of Variance (ANOVA) design was utilized to investigate limitations on visual short-term memory learning processes in computer-learning environments. Participant scores for accuracy of visual learning tasks and participant latency in responses to visual learning tasks were measured. Findings suggest achromatic color information interferes with visual STM learning tasks in specific contexts. Findings also suggest that the use of animations in visual STM learning tasks may interfere with complex visual STM learning. Numerous questions are raised for further research utilizing experimental designs that focus on visual STM learning tasks in contrast to designs that focus solely on identifying visual STM parameters.;Keywords. Computer aided instruction; Computer based instruction; Double dissociations; Dual coding; Multimedia learning theory; Information processing, Instructional design, Phonological loop, Short-term memory, Visual and spatial short-term memory, Visual stimuli, Visuospatial sketch pad, Working memory

A platform for computer-assisted multilingual literacy development

FundaWethu is reading software that is designed to deliver reading lessons to Grade R-3 (foundation phase) children who are learning to read in a multilingual context. Starting from a premise that the system should be both educative and entertaining, the system allows literacy researchers or teachers to construct rich multimedia reading lessons, with text, pictures (possibly animated), and audio files. Using the design-based research methodology which is problem driven and iterative, we followed a user-centred design process in creating FundaWethu. To promote sustainability of the software, we chose to bring teachers on board as “co-designers” using the lesson authoring tool. We made the authoring tool simple enough for use by non computer specialists, but expressive enough to enable a wide range of beginners reading exercises to be constructed in a number of different languages (indigenous South African languages in particular). This project therefore centred on the use of designbased research to build FundaWethu, the design and construction of FundaWethu and the usability study carried out to determine the adequacy of FundaWethu