introduction
During the past few decades, the expanded use of PCs and the Internet introduced many changes in human activities and cooperated in the transformation process leading from the industrial society to the knowledge society.
Among other things, the above instruments played a special role in education, and two main phases can be easily recognized: the former one where computing and ICT were mostly used to enhance individuals’ learning features (i.e., teachers mainly had the role of educational worker: planning, controlling and evaluating students’ learning processes); the latter one, more recent and centered on ICT use, where teachers had to adopt situated and collaborative learning strategies, build communities of learners (CoLs), organize students’ work for enhancing problem finding and solving, while helping the development of their ZPDs (zones of proximal development, meaning individuals’ cognitive areas marked by the distance between the subject’s knowledge/experience in a given field and the same knowledge/experience in the best skilled individuals in the community).
The above transformation modified not only teachers’ functions, but also the whole school environment and the students’ role within it.
The same ICT will help teachers and professors in finding solutions to learning problems by giving them new instruments for the analysis and continuous monitoring of students’ learning processes.
background
As already stated, computers entered very early into educational processes, often under the influence of pedagogical and psychological theories. As regards the influence of IT on individual teaching-learning processes, one of the most relevant contributions in defining the ways computers could be used in education came from Taylor (1980), who proposed three metaphors for them: tutor, tool, and tutee. The first one refers to the computer support to teachers’ work, the second one to instruments or tools autonomously used by students, and the third one to computer programming skills students must have to let problems be solved by computers. Galliani and others (1999) extended these metaphors while considering the great deal of software tools devoted to education and developed with the time. Tutor appellation describes how computer systems support or substitute (in the specific situation of auto-instruction) teachers and tutors in their work. Computer-assisted instruction (CAI), computer-assisted education (CAE), and computer-assisted learning (CAL) software are examples ofthe above systems. The former ones, CAI and CAE, implement into the topics to be taught the structure of the software the designer makes up (i.e., they force the user to follow a well-defined learning route within them); good examples for this kind of software are: 1) tools for theorems’ demonstration or physical phenomena emulation, and 2) surveying/testing software made by questions with pre-built multiple answers or yes/no answers. CAL software, with respect to the other tools, gives more importance to learning than to teaching; that is, users can now freely move within different scenarios and can decide by themselves what to do, or can browse in a personal way the context the software proposes. Good examples for these software packages are educational games, edutainment (acronym for education-entertainment) tools, simulation systems (often used for training), and many multimedia or hypermedia tools.
A further extension of tutor metaphor comes from the results of artificial intelligence application in education and especially: intelligent computer-assisted instruction (ICAI) systems and intelligent tutoring systems (ITSs). In these systems, with respect to CAI and CAL tools, there is no pre-determined teaching route or strategy, but there are three independent modules interacting among themselves: an expert (i.e., a knowledge basis on a very specific domain), a pupil (implementing the knowledge representation of a student interacting with the system), and a teacher (implementing the teacher behavior rules of everyday teaching and determining the didactic strategies to be adopted during the student-system dialogue).
With respect to the tool metaphor, its extended version now includes (together with the software students can use to produce information, i.e., editors or at most word processors) office automation suites and special tools for the analysis of a large amount of data and for browsing specific contexts (usually provided with authoring, co-authoring functions).
Finally, the extension of the tutee metaphor is mainly represented from tools for the creation of special developmental environments, such as the ones Papert created with LOGO.
It must be noted that Taylor’s metaphors and their extensions are not the only ways for interpreting the influence of computer use in individuals’ learning processes; a relevant role in the analysis of computing effects comes also from meta-cognitive hypotheses. Strictly speaking, people supporting the above hypotheses think that computer use stimulates functions’ development more than learning topics so that meta-cognitive attitudes are developed by students systematically working at a computer (Cornoldi & Caponi, 1991). Furthermore hypertexts and hypermedia, due to their features, induce the development of transversal and meta-cognitive skills.
The main feature of the educational use of IT in this phase has been the introduction of computers in school and educational systems, without any great innovation in teaching and management organization (i.e., the most relevant interventions carried out by public institutions for all levels of schools were proj ects for teachers’ training, allocation of funds for buying computing laboratories, etc.).
Radical changes in ICT influence on teaching/learning processes came from the spreading of networks and especially of the Internet (with its exponential growth in last few years). The reasons for the changes in knowledge construction hypotheses and educational effects—that is, for the passage from individual to social analysis of educational phenomena—is mostly due to computer-mediated communication (CMC) and its role on individuals, communities, and societies.
It must also be noted that the ICT influence on education can be analyzed from two different points of view: the former one looks at the possible creation of new knowledge structures; the latter one refers to the different ways ICTs can be used in learning contexts and to innovations they can induce in the same contexts.
Regarding the first point of view, many scholars proposed new definitions and interesting ideas. Rheingold (1994) proposes the concept of virtual communities as groups of individuals who can never meet themselves or physically know one another, but who use the Net for their interpersonal communication, such as for sharing information and building new knowledge. The Levy (1996) idea of collective intelligence is strongly dependent on the increase of the interpersonal communication speed and on the great amount of information the Net makes available. Furthermore Calvani and Rotta (1999, 2000), while collecting hypotheses from many other scholars, state that ICTs introduce new elements for knowledge structure—that is, it has no more only linear, sequential, closed, and hierarchical features; in addition, it also has hypertext and multimedia features. They state also that the Net extends the social negotiation aspects of knowledge and contributes in its distributed features supporting in this way the construction of meaningful learning in the subjects using it. Actually the results coming from knowledge management experiences suggest for networks and especially the Internet the role of the technical infrastructure on which a community memory (shared knowledge basis supporting a professional CoP) can be built (Trentin, 2004).
Regarding the second point, the Internet inherits and strengthens the results of previous distance education experiences and proposes for itself two main features: 1) repositories within which information, documents, and other information can be found; and 2) virtual environments where individuals can interact and build learning communities.
The above features and the improvement in education/training requests from large layers of people induced further changes in educational systems and especially universities. The definition brick-and-click university, recently introduced to describe the relevance universities assign to the presence of online courses and e-learning in their didactical offer, gives an idea of the importance ICT gained in educational contexts. But the effects of ICT on universities are not only nominalistic; they also modified the places and the actors of educational processes. Regarding the places, Ardizzone and Rivoltella (2003) hypothesize the proliferation of the environments to be used for training and suggest five possible rooms: 1) the traditional classroom, where the usual presence lesson is made or special activities like knowledge exposition, rules description, and sharing of experiences are carried out; 2) tele-didactics, that is, the teaching work strongly based on audio-video channels, with synchronous-asynchronous fruition and individual-group activities; 3) the online course, with which a virtual classroom is made and the usual teaching/learning activities are carried out without the need of teacher and/or student presence; 4) the virtual group, marked by the presence of cooperative activities within online courses and by a less important function of the teacher with respect to group interactions; and 5) the students’ community, where the role of social interactions and the multiplication of virtual groups strongly extend the students’ interactions in cyberspace.
As for the actors of educational processes, the same authors state that together with the well-known and traditional figures of teacher/professor and student (obviously with modifications in their features and functions), another professional gains importance—the tutor (in some cases two different tutors are proposed: the discipline and the system tutors).
New and old Problems In teaching with icts
It is probably too early to say if the changes induced by ICTs in higher education (especially university education) will give the right answers and solutions to the questions and problems that knowledge society puts to individuals and society.
In the author’s opinion further changes are required because many problems still unsolved ask for adequate solutions. Among them, the following ones will be analyzed: 1) the presence of preconceptions, misconceptions, and mental schemes in students’ minds; 2) the possible dependence of students’ meaningful learning from their learning styles; and 3) the assessment of students’ knowledge and skills, and the importance that portfolios have in the evaluation process.
Preconceptions, Misconceptions, Mental Schemes, and icTs
It is well known that people often manifest wrong ideas that can be interpreted in at least two different ways (Driver & Erickson, 1983): a) mental schemes, if only the coherence of people’s ideas in the interpretation of phenomena is considered (with no reference to scientific paradigms); and b) preconceptions or misconceptions (when people’s ideas are compared and evaluated with respect to the right scientific paradigms).
Studies (Cartelli, 2002) carried out all over the world with differently aged people (from students to workers, professionals, and teachers) show that:
1. Almost all disciplinary fields report the presence of wrong ideas.
2. A lot of strategies and instruments have been proposed until now to help students in overcoming the problems they meet in their study, based or not on IT strategies (like the ones described in the first part of this article), and adopting or not constructivist strategies (supported or not by ICT). A good percentage of success has been measured in those experiences. Nonetheless they were rarely compared with traditional teaching experiences and were never used systematically or adopted on a large scale in education.
3. Wrong ideas can persist in students’ minds after the above instruments and strategies have been used and the best practices have been adopted.
The author’s experience in basic computer science (CS) courses led him to hypothesize that a special e-learning platform continuously monitoring the didactic process could make easier for the students the learning of the CS topics (while giving to professors a powerful instrument for the management of their teaching). The information system the author planned and carried out (Cartelli, 2003) was very similar in its features to an e-learning platform. Most notably:
1. it had a well structured knowledge tree of the topics to be taught/learned,
2. special auto-evaluation tests, integrated within the pages of the course (they were planned on the basis of the detected wrong ideas) were available for students,
3. various communication areas implementing virtual environments for teachers/professors, tutors, and students could be accessed from everyone,
4. a careful management of the students’ evaluation and assessment tests were available for teachers, and
5. two functions for the analysis of the students’ access to the course materials and the use they made of the communication services could be used.
The management of all information in the site was guaranteed from five types of protected accesses: the system administrator, professors, tutors, students, and lastly, didactic researchers and scholars (who could only retrieve the information on the students’ access to the course materials).
The system was experimented with two different sets of students and had positive results regarding the number of students passing ending examinations; there was in fact only 20% student loss, and more than 65% ofthe students had positive, if not excellent scores. But a careful analysis of the data stored in the database showed some limits for the system: 1) many students still evidenced the presence of misconceptions (more than 43% of the whole population); 2) the amount of data generated by the second set of students (more than 300 subjects) made impossible the continuous monitoring of the didactic process by means of the two functions (reporting the number of single students or groups of them to the course materials and the temporal sequence of their access to the system).
Meaningful Learning, Learning Styles, and IcTs
It must be noted that until now, a unique definition of meaningful learning has never been proposed by scholars, but at least two main definitions are in fact available. The former one, credited to Ausubel (1990), is based on the following elements: a) logical mean-ingfulness of the topic to be learned; b) presence in that subject of special elements (subsumers), making easier the insertion of new knowledge into previous knowledge; and c) motivation to learn. The latter definition credits Jonassen (1995) with stating that knowledge construction (internal and external negotiation), context (meaningful and authentic environment), and cooperation (among students and teachers) are the basic elements for the definition of an environment leading to meaningful learning (which has to be active, constructive, cooperative, intentional, conversational, and reflexive).
Also under the hypothesis of both the above definitions of meaningful learning, no dependence has been shown until now among the development of such a learning by students, their problems, and their performances, neither in traditional contexts nor in virtual environments, online courses, and so forth.
More recently many studies have been carried out on the possible dependence of students’ success from their learning styles.
First of all the research of Kovacic and Green (2004) on a computer concepts class (at the Open Polytechnic of New Zealand) is reported here. The authors had the main aim of identifying those students requiring additional learning support and adopted for their analysis the Felder-Silverman model for students’ learning styles. After having evaluated and classified the students’ learning styles according to the Felder-Soloman Learning Style Index, the authors found statistically significant differences in performance between the different learner types they identified in their class—that is, students with reflective, sensing, verbal, and global learning preferences had the best performances both in in-course assessment and in final examination. The explanation the authors give for this result is in the advantage that the above type of learners receive from current teaching styles and the learning environment (course material and online students’ support).
Furthermore other scholars (Kumar, Kumar & Smart, 2004) used pre- and post-tests based on the Gra-sha-Riechman Student Learning Styles Scale (another model for the analysis of students’ learning styles) on a sample of 65 students (both graduate and undergraduate). They found relevant changes in the final presence of some types of learning styles with respect to the others in the class they analyzed. For the authors the observed changes depend on the instructional strategies and the technologies they adopted (i.e., the use of collaborative projects and course management software increased the number of collaborative, participant, and independent learning styles among students).
Students’ Assessment And IcTs
Knowledge society, and lifelong learning, with the continuous improvement in education and training, put the problem of a more efficient evaluation of the knowledge and skill people obtain while attending courses. The portfolio of competences has been one of the instruments developed during the last few years having great success in certifying the students’ success in educational activities. Over the last three years, there has been also a significant increase in the use of online portfolios in tertiary, secondary, primary, and professional education, to combine the benefits of traditional portfolio-based assessment with the paper-saving and other benefits of online environments. Love and Cooper (2004), while investigating the key factors necessary to design information systems for online portfolio-based assessment in tertiary, professional, secondary, and primary education, identify four weaknesses: 1) design brief omitting most of the key educational and administrative issues, and focusing mostly on identifying technical means; 2) “online portfolios” made only of a single essay, project report, or term paper presented as a Web-based electronic facsimile of a conventional document; 3) designs for online portfolio assessment systems based on an over-narrow view of value distribution that does not take all stakeholders into account; and 4) designing of online portfolio assessment systems not well integrated with overall course design processes.
In other words the authors found that online portfolio systems felt significantly short of their potential, and in many cases were inferior to conventional portfolio assessment and other more traditional assessment approaches. They suggested an alternative approach to designing online portfolio assessment systems, whose primary focus was the creation and distribution of benefits and value to all stakeholders. The main points of this alternative approach are: a) the identification of the nature and characteristics of the educational and institutional contexts for which the online portfolio assessment systems is designed (and evaluated); b) the identification of potential benefits and increase in value for all stakeholders; c) the development of heuristics for prioritizing value distributions; and d) the development of an online system through the use of best practices in course design, the fulfillment of the requirements of the course criteria, the integration of the designing of the online portfolio system with the broader course design processes, and the focus on process automation to create and distribute increased value to all stakeholders.
conclusion
The studies reported above show that ICTs can still play a relevant role in new educational fields with respect to the ones described in the background.
If further research is needed before we have solid results, it seems that the above data assign a new role to teachers/professors in the didactic process: the monitoring, analysis, and assessment of individuals’ learning processes by means of the ICT.
The examples discussed above show how the improvement of the efficacy of teaching work can be obtained with the introduction of functions (based on ICT use) analyzing the students’ data stored in an electronic repository so that:
1. The acquisition of the starting situation for each student can be easily detected and the didactic process can be personalized.
2. The change in the features of a student can be analyzed with respect to the ones of the whole population (by means of the comparison of suitable indices describing individual behaviors and learning styles, and the same indices describing the features of the whole population).
3. The change in the time of the feature s of individual students or groups of them can be detected.
4. Possible differences existing in groups of students experimenting different teaching strategies can be described, and the influence of different environments on the evolution of the teaching process can be detected.
The systematic use of ICTs in the above processes can transform teaching in an event-driven process where students’ learning styles, the use of self-assessment tests, documents produced, scores obtained, and so forth lead to the complete control of the teaching-learning process. In other words, online action-research strategies have to be adopted, and teaching teams using Web technologies (together with RDBMS and the storage of the data produced from the students accessing the Web) must be developed for a complete and successful analysis of that process.
KEY TERMS
E-Learning Platform: An information system that schools, universities, and institutions can use for teaching (only online or supporting traditional teaching) which can have the following features (all together or individually): a) be a content management system (CMS), guaranteeing the access to didactic materials for the students; b) be a learning management system (LMS), where the use of learning objects makes easier the learning of a given topic; c) be a computer-supported collaborative learning system (CSCLS), which makes easier the use of collaborative and situated teaching/ learning strategies; and d) build a virtual community of students, tutors, and professors using knowledge management (KM) strategies.
Learning Style: The personal way individuals think and learn. Also, if each individual develops a preferred set of approaches to learning, many authors suggest a well-defined set of learning models. Research seems to agree on the following elements: a) the adoption of special teaching strategies can make easier learning for students or not, depending on their learning styles; b) learning styles can evolve with individuals; and c) individuals’ learning styles can be modified by special learning environments.
Mental Scheme: The set of concepts, and dependencies among them, that individuals carry out for facing the problem of interpreting phenomena, without any reference to scientific knowledge or disciplinary paradigms.
Misconceptions (Preconceptions): Wrong ideas people manifest while explaining phenomena, with respect to scientific paradigms (i.e., people’s ideas are evaluated with respect to scientific ones). The term preconception is adopted when the wrong idea appears before people meet curricular disciplines. The term misconception is used to mark the students’ mistakes in phenomena interpretation.
Online Action Research: Uses the Internet for extending the features of traditional action research and its cyclical structure, based for many authors on five different phases: diagnosing, action-planning, action-taking, evaluating, and specifying learning. The Internet allows the continuous monitoring of action-research events and gives the researcher a further instrument to study phenomena and intervene on them.
Portfolio: The report collecting documents, scores, interviews, and so forth, and demonstrating the students’ skills, achievements, learning, and competencies, with respect to: a) previously defined areas of skill, b) specific learning outcomes from these areas, c) appropriate learning strategies that have to be developed by the student, and d) performance indicators.
Web Technologies: The set of all instruments that allows people to use the Web and its protocols for improving communication and acquiring information. These are based on hardware, which are mostly networks of computers, and software resources, which are mostly Web servers using the HTTP protocol for communicating, interfaced with RDBMS (relational data base management systems).
