Search results

In a collaborative learning environment there will be many learners with diverse cultures. These learners should be supported to communicate and collaborate among themselves. The variety of the communication and collaboration tools and modes available to each learner would depend on his/her personal cultural background. The purpose of this paper is to suggest the adaptation of the collaborative learning environment to the learner's cultural profile. So, first it aims to present learner's models with respect to his/her cultural characteristics. It also aims to present the various communication and collaboration tools and modes that would be available to the learners. Then, each learner has at his/her disposal the appropriate communication and collaboration tools and modes according to his/her cultural characteristics.

The cultural models of Trompenaars and Hampden‐Turner, as well Hofsted are modified relaxing the dualism of their dimensions. The modified models are used in a collaborative learning environment. The various attributes and types of communication and collaboration among learners and teachers in a collaborative learning environment are also identified.

This paper presents learner's cultural models across several cultural dimensions. Each cultural dimension weights differently. Also, a learner may not belong strictly to a cultural extreme of a dimension, but he/she may have characteristics from both cultural extremes of each dimension. Based on a learner's cultural profile, different communication and collaboration tools would be available to the learner.

Based on the learner's profile, either the adaptation engine, or the teacher, or the learner him/herself may select the appropriate communication and collaboration tools and modes for the particular learner. Designers, developers and evaluators of collaborative learning systems may benefit from these learners' cultural models and the communication and collaboration attributes. For example, they may create collaborative learning systems with flexible communication and collaboration attributes that provide to each learner personalized communication and collaboration tools according to his cultural profile.

This paper proposes the adaptation of the collaborative learning environment to the cultural characteristics of the learner. Future research may assign the specific communication and collaboration tools to each particular learner's cultural profile.

This paper proposes the adaptation of the communication and collaboration tools and modes that are used by a learner in a collaborative learning environment to the learner's cultural characteristics. First, the paper presents new cultural models of a learner. Then, it presents the communication and collaboration attributes and types that would be used by the learners in a collaborative learning environment. A learner would have at disposal the appropriate personalized communication and collaboration tools.

The purpose of this study is to explore the perception of the users concerning the role of artificial intelligence (AI) in enhancing personal learning profile (PLP), personal learning network (PLN) and personal learning environment (PLE) and their effect on the perceived ease of use, perceived effectiveness and perceived usefulness for enhancing the overall attitude and satisfaction of the e-learning.

The data were collected from students and professionals who have ever used the e-learning module, and smart partial least square-structural equational modeling (PLS-SEM) is used to see relations between the different variables.

It was seen that the PLE is affecting both perceived ease of use and perceived usefulness. The research has shown that perceived ease of use showed a mediating effect between PLE and attitude and satisfaction. Further satisfaction mediates between perceived ease of use and intention. PLP has come out to significantly impacting perceived effectiveness. The multigroup analysis also showed that the attitude and satisfaction level affecting intention to use the e-learning module differ across the two groups of learners, i.e. gender and type of learners.

The data are collected from students and professionals who have ever used the e-learning module and wholly based on their perceptions, leading to self-perception bias.

The current research is trying to integrate the user perception of PLP, PLN, PLE into the framework of the technology acceptance model and see how they impact the overall attitude and satisfaction of the learners. AI can be used to improve them and make e-learning more adherent to the users. AI can play an essential role in generating the right environment by matching the profile of the learner.

This paper aims to present part of the work of an ongoing research project that is looking at socio‐ cultural and technological developments from a mobile technology convergence view; in order to show how culturally aware convergence developments in mobile technology can be adopted and employed for the betterment of society.

The paper presents a scenario for a mobile technology enabled learning environment in support of the conventional learning approach with a focus on enabling parental involvement and contribution to the daily learning objectives of their children and hence enhancing a quality learning experience. It further critically discusses issues of interface design – at both the device and application levels – that will have an impact on the quality of e‐learning, with a focus on mobile technology.

The paper shows how interface design can positively enhance the quality defining characteristics of learning in an e‐learning environment. Ways of achieving these characteristics of learning through effective e‐learning are reported. This is done by addressing requirements for quality‐learning through effective interface‐design considerations, towards meeting the overall quality requirements of learning that should be intrinsic to a holistic e‐learning environment. The value of human computer interaction and the critical factors of promoting productive interaction are addressed.

There are several factors affecting quality of e‐learning as a tool and approach to flexible and independent learning. The advent and use of mobile technology has been investigated in this work from a socio‐cultural and technological perspectives in two continents. The limitations lie in the depth of investigations and how far the findings can be applied to the diversity of learners.

As the effects of cultures and the rapid technological advancements take toll on teaching and learning the findings reported in this paper have far reaching implications for learners from different cultures and also for attempts at bridging existing digital divide.

The approach adopted in the research is unique by virtue of new findings and ideas presented. The paper highlights the opportunities for mobile devices and technology to play a role in the development of communities through technology aided learning (e‐learning), with a focus on e‐learning systems and technology requirements for delivering a quality learning experience.

The purpose of this paper is to propose a conceptual model of engagement, appropriated from social media marketing, as a sense-making framework to understand engagement as a measurable process through the development of engagement profiles. To explore its potential application to education the paper follows previous work with Personalised Learning strategies to place emphasis on the promotion of the learner voice – their ability to influence decisions affecting them and their community.

This paper will position engagement as a sociocultural process and adopt an Activity Theory based methodology demonstrated through a desk analysis of VLE data from a further education college.

The analysis suggests that the approach can yield insights that may be elusive in traditional measures reinforcing the overall conceptual proposal for a multi-method approach to profiling learner engagement.

The paper has focused on presentation and exploration of the conceptual approach, which has limited the scope to broaden the discussion of the desk analysis and wider findings that this approach reveals.

It is intended that the approach offers a generalizable model that can be adopted by institutions planning to measure engagement or develop learner activity profiles. Several areas of immediate potential are identified throughout the paper.

This paper contributes a multi-method approach to engagement as argued for in recent engagement literature. This should offer institutions a way to realise value from emerging ideas within related domains of Learning Design and Learning Analytics.

Generally, the user requires customized information reflecting his/her current needs and interests that are stored in his/her profile. There are many sources which may provide beneficial information to enrich the user’s interests such as his/her social network for recommendation purposes. The proposed approach rests basically on predicting the reliability of the users’ profiles which may contain conflictual interests. The paper aims to discuss this issue.

This approach handles conflicts by detecting the reliability of neighbors’ profiles of a user. The authors consider that these profiles are dependent on one another as they may contain interests that are enriched from non-reliable profiles. The dependency relationship is determined between profiles, each of which contains interests that are structured based on k-means algorithm. This structure takes into consideration not only the evolutionary aspect of interests but also their semantic relationships.

The proposed approach was validated in a social-learning context as evaluations were conducted on learners who are members of Moodle e-learning system and Delicious social network. The quality of the created interest structure is assessed. Then, the result of the profile reliability is evaluated. The obtained results are satisfactory. These results could promote recommendation systems as the selection of interests that are considered of enrichment depends on the reliability of the profiles where they are stored.

Some specific limitations are recorded. As the quality of the created interest structure would evolve in order to improve the profile reliability result. In addition, as Delicious is used as a main data source for the learner’s interest enrichment, it was necessary to obtain interests from other sources, such as e-recruitement systems.

This research is among the pioneer papers to combine the semantic as well as the hierarchical structure of interests and conflict resolution based on a profile reliability approach.

In this paper a conception of the model for learning scenario determination is presented. We define the learning scenario as a sequence of the hypermedia pages, representing particular knowledge units, and tests related to them. The scenario determination is a dynamic process that begins when a new student takes up a course. The opening scenario for this student is chosen as the consensus of the final scenarios of the students, who have already finished this course, and who belong to a class of the learners similar to the new one. We have elaborated the consensus‐based procedure for the scenario determination. Since this procedure operates on a set of similar learners, we have developed the conceptions of learner’s profile and students’ classification. The learner’s profile is proposed to include the attributes describing students’ personal data (as name, birthday etc.), their cognitive and learning styles as well as their usage data (represented by the learning scenarios). The students’ classification is based on a set of the basic attributes that seem to influence the learning effects. Their significance is verified during the learning process. We have also elaborated the procedure of reducing undistinguishable values of the attribute and removing useless attributes from the set of basic attributes. A learning procedure proposed, describes generally the situations when the scenario is modified, and the methods used for its modification.

The International Baccalaureate (IB) programme centers on developing students' international mindedness. Central to this effort is the programme's “Learner Profile,” which details ten attributes that teachers seek to cultivate through classroom instruction. This article reports on the ways that middle grades and high school social studies and English teachers in Chicago Public Schools' (CPS) IB programmes are attempting to implement the Learner Profile as part of their classroom practice to support students' international mindedness.

The project was carried out as a two phase, sequential mixed-methods design. Phase I entailed a survey of IB teachers and programme coordinators across CPS to assess the incorporation of the Learner Profile into instruction. Phase II consisted of mixed-methods case studies of CPS IB programmes selected partially on Phase I data analysis.

We find that while teachers express high levels of familiarity with the Learner Profile attributes and confidence in incorporating them into practice, we find wide variation in the actual implementation. Taken as a whole, we find CPS programmes take divergent approaches to incorporating the Learner Profile based on differences in understanding of the attributes and its purposes as well as key organizational facets related to implementation.

Ultimately, we argue that the wide variation and lack of explicit incorporation of the Learner Profile into classrooms is related in large part to the broad, indistinct nature of “international mindedness” as a concept. The programme would benefit from creating more space for teacher and students to critique the concept, especially those working from non-Western traditions.

The purpose of this paper is to discuss how learning styles and theories are currently used within personalised adaptable e‐learning adaptive systems. This paper then aims to describe the e‐learning platform iLearn and how this platform is designed to incorporate learning styles as part of the personalisation offered by the system.

The paper discusses how learning styles and theories are currently being used within the area of adaptive e‐learning and describes current research within this area. This paper then gives an overview of the iLearn project and describes how iLearn is using the VARK learning style to enhance the platform's personalisation and adaptability for the learner. This research also describes the system's design and how the learning style is incorporated into the system design and semantic framework within the learner's profile.

The findings describe how the final implemented iLearn platform intends to address the issues found with the limited personalisation within common learning management systems and intends to provide the learner with a personalised learning experience.

Adaptability and personalisation are large research areas, however, many limitations have been found during the current research. This research project, therefore adds value to this by proposing a system which will address the current personalisation limitations.

The purpose of this paper is to develop information behaviour profiles for nursing students, to help inform information literacy programmes.

The methods include further analysis of quantitative findings (previously reported in part 1), together with qualitative research data collection and analysis. Critical incident type interviews with 11 students were transcribed and analysed using an interpretative categorisation method that used dendrograms for data display and analysis. From the regression analysis of the quantitative data, the micro-processes for information seeking were linked to learning styles, and then to personality traits to generate information seeking profiles. Integration of the qualitative findings led to development of a task-based information search model.

The start list of seven categories for qualitative analysis (derived from a literature review) was refined (one category added, one removed, with some relabelling). The quantitative data analysis revealed seven profiles (deep adventurer, deep identifier, deep investigator, strategic all-rounder, strategic collector, surface co-ordinator, surface skimmer, each linked to a particular learning style, personality trait, and preferred information seeking micro-processes).

The data were collected at only one university and the profiles and the model need to be validated with data from other groups of nursing students. The findings on micro-processes consolidate and extend previous research.

The profiles should inform information literacy programmes as they show that information search profiles may be more varied than assumed. The information search model extends previous task-based information search models.

The information search profiles have not been identified previously.

The purpose of this study is to propose a knowledge‐based mobile learning framework that integrates various types of museum‐wide content, and supports ubiquitous, context‐aware, personalized learning for museums.

A unified knowledge base with multi‐layer reusable content structures serves as the kernel component to integrate content from exhibitions for education and collection in a museum. The How‐Net approach is adopted to build a unified natural and cultural ontology. The ontology functions as a common and sharable knowledge concept that denotes each knowledge element in the unified knowledge base, and associates each learner's learning context and usage with a content and usage profile respectively. Data mining algorithms, e.g. association mining and clustering, are applied to discover useful patterns for ubiquitous personalization from these content and usage profiles.

A pilot project based on the proposed framework has been successfully implemented in the Life Science Hall of the National Museum of Natural Science (NMNS), Taiwan, demonstrating the feasibility of this framework.

This study proposes a mobile learning framework that can be replicated in many museums. This framework improves learners' learning experiences with rich related content, and with ubiquitous, proactive and adaptive services. Museums can also benefit from implementing this framework through outreach services for educational, promoting and usability needs from combining mobile and Internet communication technologies and learning services.