The ARIADNE Project (Part 1): Knowledge Pools for Computer-based and Telematics-supported Classical,Open and Distance Education

ARIADNE is a concept of computer-based and telematics-supported educational schemes. It relies primarily on a number of interconnected knowledge pools and suitable strategies for using them, in academic education—either classical or at a distance—and for certain types of corporate continuing training. In ARIADNE, the term ‘knowledge pool’ refers to a large, indexed, storage of pedagogical elements and the set of tools, methodologies and infrastructures necessary for maintaining and exploiting it, to build and distribute structured curricula. This concept is meant to address the weaknesses of many ‘open’ training schemes advocating the usefulness of unlimited and free access to the World Wide Web (WWW). In our view, this immense—but scarcely structured— document repository can all too easily become a maze and offers, in itself, little incentive to serious learning. On the other hand, ARIADNE will use a WWW based net-interface, suitable for—and inter-operable with—most platforms commonly in use by would-be learners. ARIADNE addresses two categories of users: those who contribute to the knowledge pool system and develop training curricula (professors and pedagogical engineers) and those who may enlist in and follow these curricula (students and trainees). The system's design accounts for the need for collaboration and communication between (a) trainers, to create, customize, share and reuse pedagogical documents; (b) trainers and learners, for coaching/tutoring activities and supervision of learning; and (c) students/trainees, in peer-supported learning or group work. Long-term survival of any such technology-supported education system depends primarily on motivated participants: teachers and trainers, students and trainees, academic institutions and corporations should all find some practical advantage in its use. In this paper (Part 1), we present an overview of the ARIADNE concept, describing its pragmatic educational approach and its specific approach to authoring of pedagogical material and construction of usable curricula. In a forthcoming paper (Part 2), we will address its technological approach and present a brief review of the tools needed to implement the concept as a viable computer-based and telematics-supported distance—but also open or even classical— educational system.     

The ARIADNE Project (Part 2): Knowledge Pools for Computer-based and Telematics-supported Classical,Open and Distance Education

This paper presents the tools and methodologies underlying the ARIADNE framework for enabling open and distance education and for enhancing more conventional training schemes. The ARIADNE concept relies on a distributed knowledge pool system that stores pedagogically indexed educational resources, as well as on a set of tools and methodologies for authoring curricula. The basic approach is one of share and reuse. Specialized authoring tools are under development for the production of simulations, multiple-choice questionnaires and auto-evaluation exercises. Segmentation tools for video and text-based material, with integrated facilities for hypertext generation, are also under development. The distributed knowledge pool system consists of one central knowledge pool, and a number of local knowledge pools. Corporate training systems can also be built around private knowledge pools. Before pedagogical documents can be inserted into the knowledge pool system, their pedagogical and other characteristics must be described. A pedagogical header generator tool assists in this task. Pedagogical engineers can define the spatio-temporal, socio-pedagogic process that we call a curriculum, and choose the active and expositive documents that embody it, by using a curriculum editor. Finally, students consult or work with the documents of the curriculum they subscribed to, through a personalized view provided by the ARIADNE learner interface.     

Defining attitude for science educators

A distinct and complex definition of attitude is evolving within the literature. A mental readiness to respond and a correlational consistency between attitude and behavior—although controversial and in need of further study and analysis—remain viable subcomponents within the definition. Most agree that evaluation is the heartbeat of attitude. The impact of social influence on attitudes is becoming increasingly important. Attitudes are learned and not inherited.     

Learning words through overhearing

Recent research indicates that toddlers can monitor others' conversations, raising the possibility that they can acquire vocabulary in this way. Three studies examined 2-year-olds' (N = 88) ability to learn novel words when overhearing these words used by others. Children aged 2,6 were equally good at learning novel words-both object labels and action verbs-when they were overhearers as when they were directly addressed. For younger 2-year-olds (2,1), this was true for object labels, but the results were less clear for verbs. The findings demonstrate that 2-year-olds can acquire novel words from overheard speech, and highlight the active role played by toddlers in vocabulary acquisition.     

EMPIRICAL SYNTHESIS OF THE EFFECT OF STANDARD ERROR OF MEASUREMENT ON DECISIONS MADE WITHIN BRIEF EXPERIMENTAL ANALYSES OF READING FLUENCY

Intervention researchers often use curriculum‐based measurement of reading fluency (CBM‐R) with a brief experimental analysis (BEA) to identify an effective intervention for individual students. The current study synthesized data from 22 studies that used CBM‐R data within a BEA by computing the standard error of measure (SEM) for the median data point from the baseline and intervention data. The median CBM‐R score from the intervention that the authors of each study identified as most effective fell within the SEM (68% confidence interval) of the baseline data approximately 30% of the time, but the ranges for the two author‐identified most effective interventions overlapped over 75% of the time. Extended analyses were consistent with the BEA results for approximately three‐fourths of the instances after considering the SEM of the baseline and intervention phases. Using matched passages did not improve the overlap of the ranges, but there was less overlap when the study used three data points per condition. Results emphasize the importance of considering SEM of CBM‐R data when comparing interventions within a BEA. Further implications for practice and future research are included.