Teaching new media composition studies in a lifelong learning context

Governmental proposals for lifelong learning, and the role of Information and Learning Technologies/Information Communication Technologies (ILT/ICT) in this, idealistically proclaim that ILT/ICT empowers learners. A number of important governmental funding initiatives have recently been extended to the development of ILT in further education, which provides a particularly appropriate environment for lifelong learning. Yet little emphasis is given to more problematic research findings that students may be ‘disarmed’ in the process of learning to use technology. In the current global shift towards new forms of multimedia literacy, it is important to recognize human diversity by carrying out research focusing on the actual problems students face in adapting to Web‐based technology as a new authoring medium. A case study into multimedia creative composition carried out with FE students in 1996–9 found that students tend to experience a problematic but potentially useful period of ‘creative mess’ when authoring in multimedia, and that ‘scaffolding’ strategies can be useful in overcoming this. Such strategies can empower students to derive benefits from multimedia composition if close attention is given to the setting up of the learning environment: a teachers’ model for supporting novice hypermedia authors in further education is proposed, to assist teachers to understand and support the learning processes students may undergo in dynamic composition using new media technology

Modeling peer assessment as a personalized predictor of teacher's grades: The case of OpenAnswer

Questions with open answers are rarely used as e-learning assessment tools because of the resulting high workload for the teacher/tutor that should grade them. This can be mitigated by having students grade each other's answers, but the uncertainty on the quality of the resulting grades could be high. In our OpenAnswer system we have modeled peer-assessment as a Bayesian network connecting a set of sub-networks (each representing a participating student) to the corresponding answers of her graded peers. The model has shown good ability to predict (without further info from the teacher) the exact teacher mark and a very good ability to predict it within 1 mark from the right one (ground truth). From the available datasets we noticed that different teachers sometimes disagree in their assessment of the same answer. For this reason in this paper we explore how the model can be tailored to the specific teacher to improve its prediction ability. To this aim, we parametrically define the CPTs (Conditional Probability Tables) describing the probabilistic dependence of a Bayesian variable from others in the modeled network, and we optimize the parameters generating the CPTs to obtain the smallest average difference between the predicted grades and the teacher's marks (ground truth). The optimization is carried out separately with respect to each teacher available in our datasets, or respect to the whole datasets. The paper discusses the results and shows that the prediction performance of our model, when optimized separately for each teacher, improves against the case in which our model is globally optimized respect to the whole dataset, which in turn improves against the predictions of the raw peer-assessment. The improved prediction would allow us to use OpenAnswer, without teacher intervention, as a class monitoring and diagnostic tool

Educational concept mapping method based on high-frequency words and Wikipedia linkage

We propose a computational method to support the learner's knowledge adoption based on conceptmapping relying on three perspectives of learning scenario represented by learning concept networks:learner’s knowledge, learning context and learning objective. Each learning concept network isgenerated based on a set of high-frequency words from a representative text sample that are connectedbased on the shortest hyperlink chains between corresponding Wikipedia articles. The learner exploresranking-based routings connecting learning concept networks by expanding a concept map in twocomplementing learning modes: assisted construction and assistive evaluation, with focused andcontextualized emphasis. Based on the method we have implemented a prototype of an educational tooland its preliminary testing indicated that the method can well support personalized knowledge adoption.Peer reviewe

Language acquisition and machine learning

In this paper, we review recent progress in the field of machine learning and examine its implications for computational models of language acquisition. As a framework for understanding this research, we propose four component tasks involved in learning from experience - aggregation, clustering, characterization, and storage. We then consider four common problems studied by machine learning researchers - learning from examples, heuristics learning, conceptual clustering, and learning macro-operators - describing each in terms of our framework. After this, we turn to the problem of grammar acquisition, relating this problem to other learning tasks and reviewing four AI systems that have addressed the problem. Finally, we note some limitations of the earlier work and propose an alternative approach to modeling the mechanisms underlying language acquisition

Designing Engaging Learning Experiences in Programming

In this paper we describe work to investigate the creation of engaging programming learning experiences. Background research informed the design of four fieldwork studies to explore how programming tasks could be framed to motivate learners. Our empirical findings from these four field studies are summarized here, with a particular focus upon one – Whack a Mole – which compared the use of a physical interface with the use of a screen-based equivalent interface to obtain insights into what made for an engaging learning experience. Emotions reported by two sets of participant undergraduate students were analyzed, identifying the links between the emotions experienced during programming and their origin. Evidence was collected of the very positive emotions experienced by learners programming with a physical interface (Arduino) in comparison with a similar program developed using a screen-based equivalent interface. A follow-up study provided further evidence of the motivation of personalized design of programming tangible physical artefacts. Collating all the evidence led to the design of a set of ‘Learning Dimensions’ which may provide educators with insights to support key design decisions for the creation of engaging programming learning experiences

Is concept mapping an effective tool for evaluation of student learning in science?

Concept mapping is a metacognitive learning strategy which often improves a learner\u27s ability to construct new knowledge. This action research project was intended to determine the level of effectiveness of concept mapping as a student learning intervention. Students in two high school science classes constructed concept maps before and after instruction during a unit of study about volcanoes. The maps were analyzed for increases in complexity and indications of learning. The concept maps were then compared for differences by groups based on volcano unit test scores. Based on the analysis of the matched pairs of concept maps, those maps which contained a higher amount of prior knowledge of the subject matter were associated with maps which showed greatest amount of increase in knowledge after instruction. These results are supported by the many researchers who contend that the most important factor in learning new information and gaining new knowledge is the amount of prior knowledge a learner brings into the learning situation. The results of this action research project will be applied to the development of future science courses by this researcher

The psychological dimension of transformation in teacher learning

Against a background which recognises pedagogical content knowledge as the distinctive element of teacher competence/expertise, this theoretical essay argues for its central construct - that of transformation – to be understood by teachers and teacher-educators in psychological terms (as was originally proposed by Dewey). Transformation requires teachers to fashion disciplinary knowledge such that it is accessible to the learner. It is argued that for transformation to happen, teacher thinking must include a sophisticated grasp of cognition and metacognition if teachers are to be characterised as competent, let alone expert. This article is written within a context of considerable social and academic scrutiny in the United Kingdom of the form and content of professional teacher preparation and development. In recent years the contribution of psychological knowledge to teacher-education has been filtered through procedural lenses of how best to 'manage classrooms', 'assess learning', 'build confidence' or whatever without a matched concern for psychological constructs through which such issues might be interpreted; thus leaving teachers vulnerable in their professional understandings of learning and its complexities. That society now requires high-level cognitive engagement amongst its participants places cognitive and metacognitive demands on teachers which can only be met if they themselves are conceptually equipped

The evolving link between learning and assessment : from 'transmission check' to 'learning support'

Learning and assessment are now considered as two sides of the same coin we simply cannot speak of one without also referring to the other. This paper, which traces the evolution of the link between learning and assessment, explores what led to our shift in understanding of the learning process from the behaviourist to the constructivist model, and the implications that this 'revolution ' has had for assessment. Making assessment at the service of learning is subsequently identified as the challenge ahead for the educational community.peer-reviewe