A Personalised Recommendation Framework for Ubiquitous Learning System

Pal, Saurabh; Pramanik, Pijush Kanti Dutta; Nayyar, Anand; Choudhury, Prasenjit

doi:10.1145/3460179.3460190

Cited by 6 publications

(6 citation statements)

References 18 publications

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“…Indeed, even though there are some MDA-based applications that involves certain HUD (e.g. [33], [34]), they however do not provide effective mechanisms to manage such data since they only focus on analyzing them either through datasets or by certain collected data. Generally speaking, log data are extremely diverse and processing them is unfortunately quite complex.…”

Section: Belhadad Et Al (2018) [17]mentioning

confidence: 99%

“…Finally, we compare our proposal with three research-works [33], [34], [40] that exploits HUD in pervasive environments (see Table 10). The purpose is to show the strengths of our proposed approach as well as the value added so as to improve MDA processes.…”

Section: Comparison Of Our Proposal Over Other Approaches Exploiting Hudmentioning

confidence: 99%

“…workload balancing, service availability) in particular if cloud computing techniques are involved. Thus, by considering the criteria given in Table 8, the potential strengths of our approach compared to the works presented in [33], [34], and [40] are summarized in Table 11. It should be noted that these values are assigned based on the details provided in the corresponding references.…”

Section: Comparison Of Our Proposal Over Other Approaches Exploiting Hudmentioning

confidence: 99%

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On the use of historical data in context-aware multimedia documents adaptation processes

Smaala,

Laboudi,

Saighi

et al. 2024

Bulletin EEI

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Playing multimedia documents in ubiquitous systems may require content adaptation based on gathered context information and accumulated historical data. Several approaches have already been proposed, in which adaptation actions are performed to provide adapted documents. Nevertheless, these approaches focus mainly on efficient use of context information without involving historical users data to improve the adaptation process. Thus, this paper allows for consideration of historical users data during the execution of the adaptation process. To do so, the context elements and the adaptation actions are first modeled using the oriented-object approach and then converted into relational and NoSQL databases schemes. Finally, algorithms for storing, retrieving and analysing data are designed. The proposal is validated by implementing scenarios through a real prototype. At a first step, the performances are measured to estimate the cost of data processing. The experiments show that NoSQL databases excel in data storage and ease of implementation, while relational databases perform well in data retrieve. At a second step, the proposal usefulness is highlighted by showing how historical data contribute to adaptation rules personalization using datadriven rule learning mechanisms rather than defining them explicitly. The analysis algorithm could retain personalized adaptation rules with confidence degree greater than 90%. Overall, the results are satisfactory.

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Section: Belhadad Et Al (2018) [17]mentioning

confidence: 99%

Section: Comparison Of Our Proposal Over Other Approaches Exploiting Hudmentioning

confidence: 99%

Section: Comparison Of Our Proposal Over Other Approaches Exploiting Hudmentioning

confidence: 99%

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On the use of historical data in context-aware multimedia documents adaptation processes

Smaala,

Laboudi,

Saighi

et al. 2024

Bulletin EEI

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“…Despite the availability of web search engines and in-portal searching tools, the common problem that inquiry-based learning confronts is retrieving precise information (in terms of LO) for user queries [10]. Since all search engines mostly rely on keyword-based metadata, if queries are ill-defined or missing a vital keyword, it fetches LOs that are superfluous and often fail to make any meaningful connection to the topic of a query [11]. On the other hand, even if the topic associated with the query is known, sole topic-based searching is also insufficient, as the same LO can be described under different topics at different e-learning portals.…”

Section: Introductionmentioning

confidence: 99%

Mapping Learner's Query to Learning Objects using Topic Modeling and Machine Learning Techniques

Sengupta,

Pal,

Dutta Pramanik

2023

SCPE

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Inquiry-based learning supports the independent knowledge development of the learner in an e-learning environment. It is crucial for the learner to obtain the appropriate Learning Object (LO) for the intended query. Mapping a learner's query to the right LO is a challenging task, as keyword-based searching on the topics or content does not guarantee the best result for various reasons. A query that apparently connects a topic may also implicitly refer to multiple other topics. Besides, the content of an LO with the same topic name often varies over different portals. Therefore, there is always a need for a method to automatically identify the latent topics of the query and then find the most relevant LO that covers the query. This paper aims to build a recommender system that maps a given input query to a suitable LO based on the most appropriate matching of learning contents. The proposed work employs an amalgamation of different supervised and unsupervised methods of natural language processing and machine learning. The machine learning model is trained on a handcrafted dataset to map queries into predefined topics. The proposed algorithm also leverages a dynamic topic modeling technique on learning content collected from three popular e-learning portals and uses a similarity score to map the learner's (user) query to the most appropriate LO.

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“…Flipped study room (FC) may be considered a type or a part of blended learning. Substances and technical contents are available for college students outside of the classroom via digital platforms, cloud sharing, and online Learning Management Systems (LMS) [15]. e study room conferences are planned instead of conventional lectures for brainstorming and problem-fixing discussions within the presence of the teacher/mentor.…”

Section: Introductionmentioning

confidence: 99%

A Pedagogical Framework for Advanced Learners during COVID-19 for Engineering Students

Shukla

Ahuja

Choudhury

et al. 2022

Education Research International

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The COVID-19 pandemic has raised unprecedented challenges for the progressive education community universally. One crucial challenge is the engagement of advanced learners in pandemic times. Their academic interest is retained, their performance does not decline, and they get access to appropriate resources in time. This article will elaborate on the identification mechanism and the categorization of the students grounded on their comforts and performance. The pedagogical framework is developed for advanced learners by focused interventions such as providing exposure to industry-oriented problems, international virtual events, online courses and software, career counseling by industry leaders, and preparation for higher education. In this article, we are discussing obligatory interventions and their outcomes. Adopting blended learning is becoming a boon to learners by effectively using online resources. Working with these advanced learners, the teacher can directly converse the precise space where the scholar needs the support. In this research, student-centric methods are used. A pedagogical framework is proposed for aerospace engineering students. Advanced learners are categorized into specializations based on real-time data analysis such as aerodynamics, propulsion, space technology, and avionics. Analysis suggests that the categorization and targeted pedagogical intervention yields better student performance outcomes. Based on this study, we started offering specialization-based courses at the undergraduate level in coming batches.

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A Personalised Recommendation Framework for Ubiquitous Learning System

Cited by 6 publications

References 18 publications

On the use of historical data in context-aware multimedia documents adaptation processes

On the use of historical data in context-aware multimedia documents adaptation processes

Mapping Learner's Query to Learning Objects using Topic Modeling and Machine Learning Techniques

A Pedagogical Framework for Advanced Learners during COVID-19 for Engineering Students

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