Giuseppina Rita Mangione

Automatic generation of assessment objects and Remedial Works for MOOCs

In the MOOC environments, the students feel to be alone in the process of choosing courses leading to their learning needs and work objectives. They perceive also to be controllers of their progresses with respect to calendars, fruition, assessment results. Students come into the MOOC environments to develop or enhance professional competences, to earn formative credits and to achieve certifications to get more employment opportunities, but the statistics underline high level of drop-out and few released useful credits and final certifications. These problems are mainly related to the difficulty to guarantee the “teaching presence” in courses with thousands of learners having different background and to the ineffective assessment methods for a meaningful learning process looking at the objectives and giving feedbacks for individual learning paths construction. The work, in particular, exploits the adaptation and personalization features of IWT platform in order to provide ARWE (Adaptive Remedial Work Environment) in order to fill the lack of a one-to-one tutoring mitigating the drop-out problem in MOOCs. The main original contribution of this work concerns the definition of an approach to automatically generate quizzes, exploiting a semantic-based method, in order to populate the e-Testing tool existing in ARWE, decreasing, de facto, the effort for instructors in the assessment authoring phase.

A New Model for Storytelling Complex Learning Objects

This paper focuses the attention on a particular complex learning resource, namely storytelling that is characterized by its capability to support high-level learning processes thanks to a remediation of languages, strategies and roles. In the traditional forms of storytelling, a story is told to learners in a predefined way (also known as plot). This approach is called plot-based. An alternative approach is known as character-based. The plot-based approach fails to model the dynamic behaviors of virtual characters. On the other hand, the character-based approach focuses on designing the specific behaviors or actions of the virtual characters. In this work a Storytelling Design Model is defined in order to provide pedagogy-based guidelines to the design of Storytelling Complex Learning Objects taking care of both the plot-based and character-based approaches.

Measuring Empathy to Support Learning Design and Narrative Game: A Phenomenological Approach

This work is the first step of a research aimed at the creation of instruments for empathy measurement in the learning - teaching process. In this context, the present article contributes to investigation towards the phenomenological approach to empathy concept (spatial theory of empathy[1]) and to the relationship between empathy and learning. The paper documents the choices made in the design stage of a narrative game aimed at measuring the competence of empathy. Assessment of empathy is a necessary step in a wide investigation path that could be especially useful in the design of innovative and adaptive learning experiences with a view to an ATI approach.

An Ontology-Based Approach for Context-Aware E-learning

Context-aware e-learning is an educational model that foresees the selection of learning resources to make the e-learning content more relevant and suitable for the learner in his/her situation. The research reported in this paper was purposed to improve an existing system for personalized e-learning with contextualisation features. This has been done by defining a context model, an ontology-based model to represent a teaching domain that includes contextualization information and a methodology to generate personalized and context-aware learning experiences basing on such structures.

Adaptive Feedback Improving Learningful Conversations at Workplace

This work proposes the definition of an Adaptive Conversation-based Learning System (ACLS) able to foster computer-mediated tutorial dialogues at the workplace in order to increase the probability to generate meaningful learning during conversations. ACLS provides a virtual assistant generating adaptive feedbacks, in the form of recommendations, for the conversation partners. The concepts extracted from the conversation texts trigger the recommendations, while queries on the organizational knowledge, represented by means of Semantic Web technologies, generate their content. Lastly, the Fuzzy Formal Concept Analysis is exploited to conceptualize domain knowledge.

Improving Role Taking in CSCL Script Using SNA and Semantic Web

Designing effective CSCL processes is a complex task that can be supported by existing good practices formulated as pedagogical patterns or script. Over the past years the TEE research has shown that CSCL script acts as Mediating Artifacts (MA) designing educational scenarios and structuring and prescribing roles and activities. This work proposes an approach, based on Social Network Analysis and Semantic Web, in order to improve definition and instantiation phases of IMS-LD scripts.

Unlocking Serendipitous Learning by Means of Social Semantic Web

Serendipitous Learning is the learning process occurring when hidden connections or analogies are unexpectedly discovered, mostly during searching processes (for instance on the Web) which are typical for informal learning activities, especially accomplished at the workplace context. Moreover, serendipitous processes have high probability to occur in the contexts where learners have high autonomy, more chances to intervene in different activities and to interact with resources and people. This paper proposes an approach based on the Social Semantic Web vision to sustain and improve Serendipitous Learning. The proposed approach considers two connected ontology layers to model knowledge by using several SemanticWeb vocabularies like SIOC, Dublin Core, SKOS, and so on. The SKOS role is particularly relevant because it allows connections among heterogeneous resources, also across multiple communities. The proposed approach models the above-mentioned connections at the conceptual level and facilitate learners in discovering them and following unexpected paths.

A model for generating personalised learning experiences

The paper put its focus on personalised learning experience showing a specific model that take into account both the Context Profile and the Learner Profile. The learner model also facilitate the identification of learning gaps in current job role and the delivery of appropriate, individualised learning plans. Moreover, even as we speak, the adoption of Web 2.0 approach emphasised the central role of the user and more in general the user generated contents. In order to benefit from this digital era vision from the learning point of view, we need tools and solutions that support us in dominating the technologies in order to serves our purposes and need to codify to improve interactions which influence intangibles. We have to go further than the state represented below (moving towards dynamic personalised learning experience).

Disaster Education: a narrative-based approach to support learning, motivation and students’ engagement

Over the last decade, the interest in disaster education has grown rapidly. Several studies demonstrate that effective results can be obtained in this field only with instructional methods able to motivate the learner and to support them in practicing skills by means of narrative situations. The narrative is a privileged method that can help developing cognitive skills, organize knowledge and support the construction of meaning. In this paper we present a novel adaptive storytelling model defined in the context of ALICE project and its contextualization in the field of disaster education. The defined model aims at maximizing learner’s understanding and development of concepts fostering the “learning in action” and problem solving skills in natural disaster contexts by combining direct experience, observation, discovery and action. In particular the model arises motivation in the story and creatively engage learners in finding solutions to a problem and building personal responsibility. The experimentation results are encouraging and confirm that the storytelling offers higher engagement than the traditional practicing methods.

Metacognitive Learning Environment: a semantic perspective

In the last years, Knowledge Technologies have been exploited to realize innovative and challenging self-regulation scenarios in e-learning systems. The learning environments as metacognitive artifact suitably scaffolding learners to improve their self regulated abilities, is still lacking though. In this work, we propose an innovative Web-based educational environment that sustains metacognitive self-regulated learning processes by means of Semantic Web and Social Web methods and technologies.