1. Interaction. The interactions learners have with each other build interpersonal skills, such as listening, politely interrupting, expressing ideas, raising questions, disagreeing, paraphrasing, negotiating, and asking for help. 2. Interdependence. Learners must depend on one another to accomplish a common objective. Each group member has specific tasks to complete, and successful completion of each member’s tasks results in attaining the overall group objective.

将“Cooperative Learning”融入课堂——浅谈英语素质教育

This paper describes emergent learning and situates it within learning networks and systems and the broader learning ecology of Web 2.0. It describes the nature of emergence and emergent learning and the conditions that enable emergent, self-organised learning to occur and to flourish. Specifically, it explores whether emergent learning can be validated and self-correcting and whether it is possible to link or integrate emergent and prescribed learning. It draws on complexity theory, communities of practice, and the notion of connectivism to develop some of the foundations for an analytic framework, for enabling and managing emergent learning and networks in which agents and systems co-evolve. It then examines specific cases of learning to test and further develop the analytic framework. The paper argues that although social networking media increase the potential range and scope for emergent learning exponentially, considerable effort is required to ensure an effective balance between openness and constraint. It is possible to manage the relationship between prescriptive and emergent learning, both of which need to be part of an integrated learning ecology.

/pdf/emergent-learning-and-learning-ecologies-in-web-2-0-1mk7zeq5el.pdf

Emergent learning and learning ecologies in Web 2.0

Knowledge sharing is an activity through which knowledge, namely, information, skills, or expertise, is exchanged between people, friends, families, communities or organizations. Online knowledge sharing activities are flourishing with the advent of social media and digital life. However, despite of the importance of the online knowledge sharing methods and mechanisms, there is not any comprehensive and systematic study about studying and analyzing its important techniques. Therefore, the main aim of this paper, the comprehensive, detailed, and systematic study, and survey of the state-of-the-art knowledge sharing mechanisms in an online environments is provided. Also, this paper presents a systematic literature review (SLR) on the online knowledge sharing literatures up to end of 2015. We identified 348 papers, which are reduced to 251 primary studies through our paper selection process. Also, the broad overview of the literature provides insights into potential areas for further research. By providing state-of-the-art information, this survey will directly support academics and practicing professionals in their understanding of developments in online knowledge sharing mechanisms and techniques.

/pdf/online-knowledge-sharing-mechanisms-a-systematic-review-of-wjgml934hb.pdf

Online knowledge sharing mechanisms: a systematic review of the state of the art literature and recommendations for future research

Artificial intelligence (AI) has penetrated every layer of our lives, and education is not immune to the effects of AI. In this regard, this study examines AI studies in education in half a century (1970–2020) through a systematic review approach and benefits from social network analysis and text-mining approaches. Accordingly, the research identifies three research clusters (1) artificial intelligence, (2) pedagogical, and (3) technological issues, and suggests five broad research themes which are (1) adaptive learning and personalization of education through AI-based practices, (2) deep learning and machine Learning algorithms for online learning processes, (3) Educational human-AI interaction, (4) educational use of AI-generated data, and (5) AI in higher education. The study also highlights that ethics in AI studies is an ignored research area.

Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century

Some rule based techniques are presented that can assist powered wheelchair drivers. The expert system decides on the direction and speed of their wheelchair. The system tends to avoid obstacles while having a tendency to turn and head in towards a desired destination. This is achieved by producing a new target angle as an extra input. Other inputs are from sensors and a joystick. Directions are recommended and mixed with user inputs from the joystick representing desired direction and desired speed. The rule-based system decides on an angle to turn the powered wheelchair and suggest it. Inputs from the joystick and sensors are mixed with the suggested angle from the Rule Based Expert System. A modified direction for the wheelchair is produced. The whole system helps disabled wheelchair users to drive their powered wheelchairs.

/pdf/a-rule-based-expert-system-to-decide-on-direction-and-speed-323ep0om46.pdf

A rule-based expert system to decide on direction and speed of a powered wheelchair

Research on the role of grit – defined as both perseverance and passion for long-term goals – on human performance has been conducted for the past decade. It has been suggested that this non-cognit...

/pdf/the-study-of-grit-in-engineering-education-research-a-2aarjfbz3y.pdf

The study of grit in engineering education research: a systematic literature review

During their final year undergraduate project a student may feel under-supported, stressed or isolated. In an internally funded project we set out to investigate the benefits of using a diverse blend of collaboration and communication tools alongside traditional methods of final year project supervision. We established separate formal and informal communication channels between the supervisor and their project students and a community of practice of students and supervisors was set up using twitter or a web forum. Using a wiki as a collaborative workspace and repository, student project pages were created and virtual supervision was blended with face-to-face supervision using electronic logs. at first some students were dubious about our approach and disapproved of at least one of the tools used. The supervisors were also initially sceptical of an increase in workload due to the multiplicity of tools used. In this paper we present how the staff and students benefited precisely because of the diverse range of tools used. The methods used resulted in transparency of students’ and supervisors’ actions, however, lessons were learnt about how to address student concerns about plagiarism in such an open environment.

/pdf/a-two-year-case-study-technology-assisted-project-17t31eiciz.pdf

A two year case study: Technology Assisted Project Supervision (TAPaS)

A quantitative and qualitative empirical evaluation is presented to show the effect of providing some sensor support during driving lessons as a tele-operator learns to drive a mobile robot. Different levels of sensor support were provided and the effect on training was measured. Different levels of force feedback were provided through a joystick. Results are presented and conclusions drawn about the way that tele-operators behave during driving tasks.

/pdf/adjustment-of-tele-operator-learning-when-provided-with-1ml2ru9inv.pdf

Adjustment of Tele-Operator Learning When Provided with Different Levels of Sensor Support While Driving Mobile Robots

This paper investigates whether the use of sensors throughout training is more effective than not. Results are presented from investigating novice vehicle drivers learning while using varying amounts of sensor support. Qualitative and quantitative data evaluations are made to compare drivers with sensors against those while they learn to drive a vehicle. Dependence on the training methods used was logged as a different amount of support given by the intelligent systems. The work reflects on whether experienced drivers taught with sensors aiding them during their training, were then able to drive satisfactorily when they later did not have any assistance. Some results are included and, in all situations, assistance was more advantageous as driving tasks became more difficult.

/pdf/learning-to-drive-with-and-without-intelligent-computer-2s1s0dw34k.pdf

Learning to drive with and without intelligent computer systems and sensors to assist

Different students approach tasks in a project differently Supervisors need to devise ways of accommodating these differences, albeit the difficulties in identifying them At the start of a project, a student may be a) Independent and need very little supervision, b) Collaborator and seek supervision as required, c) Poser who poses to be independent and may seek help later or the supervisor may need to identify and provide help, d) Dependent on the supervisor They do not however stay in these categories throughout the project The supervisor must identify and help those students in categories other than (a) We present a novel mix of social software namely: Twitter and Wiki The aim is to help supervisors in identifying their student’s needs thereby making them more flexible in dealing with different students Students themselves get greater sense of ownership and community support from fellow students doing a project

/pdf/work-in-progress-use-of-social-software-for-final-year-1vw880twz2.pdf

Manish Malik

Papers

The study of grit in engineering education research: a systematic literature review

A two year case study: Technology Assisted Project Supervision (TAPaS)

Adjustment of Tele-Operator Learning When Provided with Different Levels of Sensor Support While Driving Mobile Robots

Learning to drive with and without intelligent computer systems and sensors to assist

Work In Progress: Use of Social Software for Final Year Project Supervision at a Campus Based University