Adaptive Technologies for Learning & Work Environments (2001)

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This book includes key information on personality assessment and coping skills. It helps you identify assistive solutions matching users needs. It lists many funding sources, support organizations, publications, and technology vendors in a comprehensive resource directory. This book is an indispensable reference guide for anyone using or working with assistive technology.

Olson, et al. It explains how technologies can be adapted and how different devices can work together.

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This book will be especially helpful to healthcare and medical professionals as many topics covered pertain to patient care. This book is a useful resource for special educators and parents. July The author does a thorough job of describing the various technology options available to persons with visual, hearing, motor, speech, or learning disabilities. This book includes an evaluation of more than products.

It also discusses strategies for funding adaptive technology and offers cost-saving tips. The author provides a good overview of available technologies, offers tips for applying for funding, and gives pointers to locate equipment vendors. This book will undoubtedly help you get started with assistive technology. Through a series of case studies, the author does a masterful job of describing how assistive technology affects the lives of disabled persons. This book highlights the issues surrounding the implementation and the use of assistive technology.

It also offers practical steps for matching a person with the most appropriate devices. A 'must read' for anyone assessing assistive solutions for people with disabilities. Primarily meant for educators working with visually impaired students, this book provides several assessment worksheets to help you select appropriate technologies and devices. If you're looking to initiate or expand the use of access technology in your school, you will need this book. Flippo, et al. The three-semester design-based research process as well as the multiple instances of implementing designs within each iteration allowed explanations for effects to be constructed and validated via repeated observation.

In order to promote validity multiple sources of data were used to form conclusions lesson recordings, teacher observations, student feedback and the analysis was critically reviewed by a number of national and international experts as part of a doctoral program.

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This study is conducted in the context of teaching and learning introductory computer programming as part of an online Graduate Diploma of Information Technology GDIT at Macquarie University. As part of the semester long subject students completed a two-hour weekly online class where they learnt the fundamentals of writing computer programs in Java. As a four credit point graduate course the pace and amount of content covered was greater than an undergraduate introduction to programming course, covering basic programming syntax and semantics, objects and classes, polymorphism and inheritance, Applets and GUIs, arrays and ArrayLists, as well as error handling and file operations.

Students who undertook the online GDIT were graduate students or students with commensurate professional experience that qualified them to enter the course from a discipline other than computing that wished to extend their IT knowledge and skills. There were 26 students who enrolled across the three semesters that were analyzed in this study, of which 20 completed the unit. Of the 20 students who completed the subject, ten were enrolled in Semester 2, seven in Semester 1, and three in Semester 2.

Of the 26 students, 9 were female and 17 were male. Adobe Connect includes a range of tools through any Flash enabled browser including those to present documents, to broadcast webcam and voice, to screen share, to exchange text chat and files, to vote, as well as those providing a shared notes space and whiteboard. This provides the session host with ultimate choice over the tools that are provided within an interface and the way that they are arranged, allowing the interface to be dynamically redesigned to meet the evolving requirements of the learning episode.

A default layout is shown in Figure 1. Each room comes with three predefined layouts, which the host can switch between by toggling tabs at the bottom of the browser window. As well, new layouts can be created so that a room can have several pre-designed layouts or layouts can added on the fly. Copies of room designs can be created with relative ease and several rooms can run at once, providing separate working spaces for collaborative group-work. Finally, all sessions have the capacity to be recorded, on which basis the data for this study has been harvested, analysis performed, and results derived.

Results have been derived by organizing and describing key observations from the three semesters in order to demonstrate the evolving understanding of how adaptive design could be used to cater to the emerging cognitive and collaborative requirements of the learning episodes. Based on these observations, principles for design of multimodal synchronous online learning environments and the framework for adaptive learning design are described in the Discussion section.

Even though predominantly transmissive approaches were adopted in Iteration 1, there were still times where reasonable levels of student contribution arose, for instance in the form of responses to questions from the teacher. In cases where the number of contributions was high it was sometimes necessary to adapt the interface to better accommodate the amount of text-chat arising, even if individuals were only making short factual contributions. For example, in Figure 1 the teacher is presenting the solutions to tutorial questions using direct instruction approaches.

Then at one point a degree of student participation was encouraged by asking them to contribute their answers to the factual style questions by typing responses in the text-chat pod. As a result the teacher chose to enlarge the chat pod and place it along the bottom section of the browser window see Figure 2. In the lesson students indicated that enabling more text-chat contributions to be viewed at once represented an improvement to the interface.

One student also made the suggestion to elongate the attendee pod in the interface shown in Figure 2 to utilise the empty space and to allow students to immediately see who else was in the room. This suggestion was subsequently enacted, again improving the ability for participants to interact. This episode not only illustrated how the size of pods could influence collaboration in the learning environment, but also how the students as the end-user of interface could be critical sources of in-situ interface design ideas.

Student observations and design suggestions were derived from their actual attempts and experiences using the interface rather than from estimating the student experience in advance as is the traditional context of the educational designer. To facilitate the practical activities, the interface was often changed to desktop broadcasting mode so that the teacher could model programming processes as exemplified in Figure 3.

Introduction: passive brain-computer interfaces for adaptive digital environments

By switching to the screen-share layout at times when students had questions about programming processes the teacher was able to show them a range of practical skills relating to writing and running computer programs. This allowed students to efficiently develop their procedural knowledge in cases where they had little or no previous understanding of how to program. The teacher could use audio to provide insight into underlying thought processes in a more cognitively efficient manner than if text-chat was being used.

However, the transmissive nature of the approach meant that students had little opportunity to practise their programming skills, and as such the teacher could not accurately diagnose student problems or provide remedial instruction. Iteration 2 was characterised by redesigning the environment to facilitate more student-centred pedagogies. For instance, in the second online tutorial students were divided into two rooms and asked to construct a group answer identifying the classes, objects, instance fields, methods and local variables in a program. The interface was redesigned to provide the program in the middle column of the window, a communal solution space in the top right note-pod and a text-chat pod at the bottom right of the interface.

A shared solution space was provided in order to allow activity to centre around students rather than the teacher see Figure 4. Iteration 2 Topic 2 Purpose built interface to facilitate student-centred sharing of declarative knowledge. Students in both groups were able to complete this exercise in their teams, negotiating collaborative solutions to the factual knowledge task. The teacher was able to review the group-work room note pods and text-chat transcripts to identify any misconception and then attend to these once students had returned to the main room.

As opposed to the teacher delivery approach that had been adopted in Iteration 1, the redesign of the environment had enabled far greater levels of student engagement and collaboration about the foundational subject matter knowledge. In other instances students were provided with authentic programming process tasks that required them to build solutions in teams.

In order to accomplish this the environment was redesigned to provide each group with their own room and increased permissions so that they could add and share their computer code. For instance, in Figure 5 below students were divided into groupwork rooms and asked to complete the following task:. Write a class TinCan that creates cylindrical TinCan objects and has a method to return the volume. Write a class TinCanTest to test your class. Instructions were provided as part of the interface design to avoid split attention.

However those two students had not been given prior instruction on how to facilitate such an activity, and as a consequence there were some skills that they lacked relating to effectively collaborate while using screen sharing. As well, the teacher had not considered that without audio they would not be able to respond to their peers using text-chat without switching focus from the IDE that they were broadcasting. If the teacher would have anticipated the collaborative requirements of the learning episode in advance then students could have been trained in the use of audio and directed to use it.

Students in both groups were highly engaged by the student centred task. However their collaborative efficiency was compromised by the interface design and their incomplete technological skills, which were in turn rectified in future lessons by enabling student audio and providing them with prior practice in using it. In order to allow students to more effectively work between multiple programming files the interface was often redesigned to incorporate several program files at once.

For instance, in the activity shown in Figure 6 below, students were required to combine a resize circle program and re-centre circle program into one applet so that a circle could be both re-centred and resized. For this interface the resize and re-centre programs were displayed in note-pods, and a third note-pod column was provided for students to write their combined program.

The layout allowed all the relevant information to be accessed from the one interface, resulting in less split attention than when the IDE is used. Once again the text-chat discourse allowed the teacher to easily review collaborations that had transpired in each room.

The interface supported high levels of student contribution by providing spaces for people to collaboratively problem solve and discuss concepts. In this exercise Group 1 contributed 52 comments and Group 2 contributed 78 comments, which was several times more than in the more transmissive approach adopted in Iteration 1. Once the relevant code from the re-centre and resize program had been incorporated into the solution space, the pods containing the code became redundant.

This led to Group 2 also spontaneously deciding to maximize the pod containing the integrated program to cover the other obsolete note-pods see Figure 7. This is an example of interface flexibility affording the capacity to dynamically adjust the interface to suit the changing collaborative and cognitive requirements of the activity Hollan, et al. While the approaches above enabled more efficient collaboration for programming processes, it did not directly respond to conceptual difficulties that students were experiencing.

In Iteration 3 whiteboards were used, often spontaneously, to support concept development. Whiteboards allow persistent visual presentation and interrelation of several items of information. The poor progress was partially due to their difficulty understanding mathematical concepts relating to centring the circle. In order to provide a clearer explanation of the coordinate geometry underlying the task, the teacher chose to spontaneously use a whiteboard to represent the situation see Figure 8. Iteration 3 Topic 8 Spontaneous inclusion of a whiteboard to support discussion of visual concepts.

Having the whiteboard next to the note pod enabled the programming code to be directly compared to the concept being addressed, allowing students to interrelate the syntax of the programming language with its semantic meaning. As a result of the adaptive redesign students were able to better understand the programming concepts with which they were working and henceforth completed the programming process expeditiously. Whiteboards were often introduced to represent dynamic concepts.

They allowed the teacher and students to step through programs and emulate their operations. For instance, at one point in the subject students were required to write a program that produced random permutations of the numbers from 1 to Students still indicated uncertainty about the underlying logic of the program, so the teacher chose to use a whiteboard to allow the group to emulate the operation of the code see Figure 9.

Iteration 3 Topic 11 Second use of whiteboard to support dynamic representation of conceptual information. The whiteboard allowed the process of element extraction from a random position in anArray originally containing numbers zero to nine in ascending order and placed in a second array while the last element in anArray is shifted to the gap created by the extraction. Students could perform the next step in the program in order to demonstrate their level of understanding.

The public solution space allowed cognition to be offloaded to the environment Hollan, et al. The approach allowed the program and general process of using arrays to perform selections to be comprehended by students whereas in previous iterations explanations had been poorly understood. At other times in Iteration 3 learning commenced with conceptual discussion and progressed to more practical application of processes that applied those concepts. In such cases whiteboards could be used as a starting point to represent the conceptual information before transitioning to screen sharing to perform programming processes.

Initially a transmissive approach was adopted, but midway through the explanation the teacher asked if students had any questions. This resulted in a number of questions, for instance about whether variable names needed to correspond between programs, whether constructors could be different for the two classes implementing the interface, and general questioning relating to strategic interface design.

In order to demonstrate their understanding the students were required to add a Colour interface to the original polymorphism example. This was conducted as a teacher-led programming activity, which differed from Iteration 1 and Iteration 2 where it was an independent activity and group-work activity respectively. A standard sharing interface was used with the teacher broadcasting the IDE see Figure 11 , and students were required to instruct the teacher what to do next in order to solve the problem.

The teacher-led approach enabled a considerable amount of student questioning and contribution to be elicited, thus allowing the teacher to gauge that students ultimately understood the concept. In Iteration 3 students were also provided with the opportunity to collaboratively negotiate concepts as a way of taking ownership over them. The approach encouraged students to collaborate with one another and the productive nature of the task allowed their mental models to be revealed. Students indicated that the approach clarified their understanding of the difference between shallow and deep copying.

In Iteration 3 students were given more guidance on how to share their screen and were encouraged to use audio throughout.


This enabled students to demonstrate their programming process capabilities and collaboratively solve programming problems. For instance in an activity requiring the development of a program that allows users to select the input file at runtime using a JFileChooser, initially students used a notes-pod approach much like that in Figure 6 and Figure 7.

This allowed students to rapidly combine their ideas with equal access to the solution space. However the approach did not enable them to collaboratively test their program and resolve errors in their code. Subsequently a student volunteered to lead the debugging process, changing the interface so as to broadcast their screen see Figure This allowed students to represent their procedural understanding through the activity performed as part of the negotiated desktop sharing process, as well as their conceptual understanding through their collaborative programming discussions.

The teacher was able to perceive the extent of student understanding, and that together they had mastered the ability to apply the concepts to solve a real-life problem.

Adaptive Technologies for Learning and Work Environments, Second Edition

The task was completed with the student leading the exercise, the group responding, and the teacher contributing occasionally. While the descriptions and examples above cannot fully explicate the design-based research process, observations and results, it does provide an indication of the nature of the data collected and the type of analysis that was conducted.

A more complete portrayal is available online for readers who may be interested Bower, The ability to select the combinations of modalities that will be used to facilitate interaction and knowledge representation in many synchronous learning environments means educational designers have a strong influence over the collaboration and learning that transpires.

The ability to adaptively design some of these multimodal learning environments affords the potential to tailor the interface to meet the evolving collaborative and cognitive requirements of the learning episode. On the basis of the observations and analysis conducted in this study, principles for design of multimodal synchronous learning environments are outlined below. This is followed by a framework for adaptive learning design, based on the level of interaction anticipated and the type of knowledge being represented.

Different representational possibilities are afforded by different modalities. Evidence from this study suggested that the modality of representation should be selected to match the cognitive and collaborative requirements of the learning episode as follows:. The design of effective multimodal clusters was observed to rely upon application of multimedia learning principles Mayer, a. Examples include:. Because students were discussing curriculum matter more extensively and producing solutions in student-centred tasks during Iteration 2 and Iteration 3 their mental models were more fully revealed.

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This provided the teacher with greater insight into the accuracy of student schema and the form of remediation that may be required. Students were able to practice subject specific processes and co-construct understandings with one another. Successful learning may depend on having a balance of transmissive, interactive and collaborative activities, however the efficacy of lessons where student contributions are not made on a frequent basis should be carefully considered.

In such circumstances it is not possible to ascertain the level of student engagement or understanding. This is particularly pertinent in online environments because of the lack of non-verbal cues such as body language. Relevant tasks require students to integrate different levels of knowledge and encourage collaboration through their goal oriented and problem solving nature. Establishing clear expectations about the nature of the collaboration required allows students to concentrate on the task rather than how to interact using the mediating technology.

Strategies include providing clear task specifications, allocating students to roles, ensuring students have the required technological competencies to perform the task, and suggesting ways to represent concepts using the technology. By pre-empting areas where students will require explicit instructions on how an exercise should be performed or providing support in-situ, students are able to dedicate more time to developing their design and problem solving abilities unimpeded by overheads incurred by trying to learn collaboratively in online mode.

Providing collaborative space both virtual and temporal increases the amount of contribution students can make during a learning episode. Along with providing student-centred authentic tasks, providing students with adequate collaborative space was critical to revealing their mental models so that the teacher could more accurately diagnose misconceptions and provide appropriate feedback.

In conversational approaches to learning the direction of discourse is negotiated Laurillard, This means that the cognitive and collaborative requirements of the interface may change based on the interpretations, actions and feedback of participants. This makes it imperative that the interface is redesigned during learning episodes in order to meet the evolving representational and interactional needs, wherever possible.

Examples include using whiteboards to represent emerging requirements for conceptual discussion, using screen broadcasting to perform group programming processes, using notes pods to work with larger quantities of factual information. At times text-chat was sufficient for a few students to contribute factual responses, however for more extended, tightly coupled interactions involving intensive use of another visual medium then audio was more suitable to allow more rapid contribution and more cognitively efficient information processing.

Students can an excellent source of redesign ideas, often contributing suggestions and adjusting the interface themselves when given the opportunity. For instance, in Iteration 2 and Iteration 3 of the student-centred Circle Applets programming activity, students decided to enlarge the note-pod of the main program. Once the other programs are integrated into the main program they become obsolete, and enlarging the combined program allowed a more complete view of the code. Resizing pods allowed their relative level of importance in the shared cognitive process to be represented.

The fact that students are frequent users of the environment for learning means that they can often generate environmental adaptations that had not been considered by the teacher. While these principles have been derived from studying teaching and learning via web-conferencing, it is proposed that they can be transferred to some extent to other online learning environments. The analysis conducted in this study implies a framework for adaptive design in web-conferencing environments based upon the level of interaction to be facilitated and the level of knowledge being addressed.

Table 1 contains thumbnail summaries of the techno-pedagogic patterns that comprise the web-conferencing learning design framework. The summaries are patterns in so far as they provide a description of how the learning environment may be redesigned depending on certain attributes knowledge and interaction type but generalizable to a range of learning situations for instance, different domain of study. The patterns are atomic in so far as they operate at the level of individual learning activities rather than larger session, module or program patterns.

By defining a series of nine design patterns for different types of activity and different levels of knowledge the framework supports rapid redesign based on the emerging requirements of the learning episode. Dominic, M. Ford, N. Individual differences, hypermedia navigation, and learning: an empirical study. Journal of Educational Multimedia and Hypermedia, 9 4 , Froschl, C.

User modeling and user profiling in adaptive e-learning systems Unpublished master thesis. Graz University of Technology, Austria. Graf, S. Learning styles and cognitive traits-Their relationship and its benefits in web-based educational systems.

Computers in Human Behavior, 25 6 , Hung, S. Exploring e-learning effectiveness based on activity theory: An example of asynchronous distance learning. Kim, M. Adaptive e-learning environments: theory, practice, and experience. Modritscher, F. In Proceedings of the international conference on interactive computer aided learning ICL Murray, T. MetaLinks: Authoring and affordances for conceptual and narrative flow in adaptive hyperbooks.

International Journal of Artificial Intelligence in Education, 13 , Park, O. Adaptive instructional systems. Jonassen Ed. Handbook of Research for Educational Communications and Technology pp. Mahwah, NJ: Lawrence Erlbaum. Popescu, E. Adaptation provisioning with respect to learning styles in a web-based educational system: an experimental study. Journal of Computer Assisted Learning, 26 4 , — Premlatha, K. Dynamic learner profiling and automatic learner classification for adaptive e-learning environment.

Interactive Learning Environments, 24 6 , Rosenberg, M. E-learning: Strategies for delivering knowledge in the digital age Vol.

Adaptive Technologies for Learning & Work Environments (2001) Adaptive Technologies for Learning & Work Environments (2001)
Adaptive Technologies for Learning & Work Environments (2001) Adaptive Technologies for Learning & Work Environments (2001)
Adaptive Technologies for Learning & Work Environments (2001) Adaptive Technologies for Learning & Work Environments (2001)
Adaptive Technologies for Learning & Work Environments (2001) Adaptive Technologies for Learning & Work Environments (2001)
Adaptive Technologies for Learning & Work Environments (2001) Adaptive Technologies for Learning & Work Environments (2001)
Adaptive Technologies for Learning & Work Environments (2001) Adaptive Technologies for Learning & Work Environments (2001)
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