Recommender system for learning SQL using hints

Lavbič, Dejan; Matek, Tadej; Zrnec, Aljaž

doi:10.1080/10494820.2016.1244084

Cited by 13 publications

(7 citation statements)

References 30 publications

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“…Previous studies have shown that there are challenges and difficulties in the learning of SQL [44,45,19,18]. To ensure considerable practice as proposed by [19], a formative assessment system should pre-assess students' prior learning before the start of a new learning, and where there are gaps, recommend materials for more practice.…”

Section: B Logic Based Rules Formalism For Classificationmentioning

confidence: 99%

Formalizing Logic Based Rules for Skills Classification and Recommendation of Learning Materials

Ehimwenma¹,

Crowther²,

Beer³

2018

IJITCS

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First-order logic based data structure have knowledge representations in Prolog-like syntax. In an agent based system where beliefs or knowledge are in FOL ground fact notation, such representation can form the basis of agent beliefs and inter-agent communication. This paper presents a formal model of classification rules in first-order logic syntax. In the paper, we show how the conjunction of boolean [Passed, Failed] decision predicates are modelled as Passed(N) or Failed(N) formulas as well as their implementation as knowledge in agent oriented programming for the classification of students' skills and recommendation of learning materials. The paper emphasizes logic based contextual reasoning for accurate diagnosis of students' skills after a number of prior skills assessment. The essence is to ensure that students attain requisite skill competences before progressing to a higher level of learning.

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Section: B Logic Based Rules Formalism For Classificationmentioning

confidence: 99%

Formalizing Logic Based Rules for Skills Classification and Recommendation of Learning Materials

Ehimwenma¹,

Crowther²,

Beer³

2018

IJITCS

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“…• Group 3: 33 learners. (Lavbič, Matek and Zrnec, 2017) propose a new approach to help users learn SQL easily. The analysis was performed on a database of 93 learners.…”

Section: Other Recommendation Systemsmentioning

confidence: 99%

Recommendation Systems on E-Learning and Social Learning: A Systematic Review

Souabi¹,

Retbi²,

Idrissi³

et al. 2021

EJEL

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E-learning is renowned as one of the highly effective modalities of learning. Social learning, in turn, is considered to be of major importance as it promotes collaboration between learners. For properly managing learning resources, recommender systems have been implemented in e-learning to enhance learners' experience. Whilst recommender systems are of widespread concern in online learning, it is still unclear to educators how recommender systems can improve the learning process and have a positive impact on learning. This paper seeks to provide an overview of the recommender systems proposed in e-learning between 2007 and the first part of 2021. Out of 100 initially identified publications for the period between 2007 and the first part of 2021, 51 articles were included for final synthesis, according to specific criteria. The descriptive results show that most of the disciplines involved in educational recommender systems papers have approached e-learning in a general way without putting as much emphasis on social learning, and that recommender systems based on explicit feedbacks and ratings were the most frequently used in empirical studies. The synthesis of results presents several recommender systems types in e-learning: (1) Content-based recommender systems, (2) Collaborative-filtering recommender systems, (3) Hybrid recommender systems and (4) Recommender systems based on supervised and unsupervised algorithms. The conclusions reflect on the almost lack of critical reflection on the importance of addressing recommender systems in social learning and social educational networks in particular, especially as social learning has particular requirements, the weak databases size used in some research work, the importance of acknowledging the strengths and weaknesses of each type of recommender system in an educational context and the need for further exploration of implicit feedbacks more than explicit learners’ feedbacks for more accurate recommendations.

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“…As a possible teaching approach to database concepts, one could use intelligent tutoring systems and interactive learning environments such as [9,11,12,23,29,30], but since the aim of our study is to analyze learning outcomes for basic CLR concepts when using different notations, we did not elaborate on these approaches in detail.…”

Section: Related Workmentioning

confidence: 99%

Experimental study on the effectiveness of a teaching approach using barker or Bachman notation for conceptual database design

et al. 2018

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Relational databases are one of the pillars of information systems and as a consequence conceptual and logical design can be seen as the foundation of almost every application regardless of the platform. Nevertheless, little research has been done so far on the effectiveness of teaching approaches to database basic concepts and design. This paper introduces a multi-level experimental study developed to examine the effectiveness of learning database fundamentals, depending on the notation used for conceptual design. The main experiment was carried out at a higher education institution. We developed different experimental instruments to evaluate the effectiveness of a teaching approach using Barker or Bachman notation for conceptual database design. In contrast to Barker notation, Bachman notation incorporates elements of logical design (i.e. foreign keys) in the conceptual design level. Students' achievements were examined with regard to influencing factors throughout the learning process. Introducing the Bachman notation and a manual transformation from a conceptual into a logical data model, could increase students' understanding of conceptual, logical and relational data model concepts. We found that the notation used during the learning process has an impact on students' achievements. Moreover, students achieved better results when solving tasks presented with a notation that incorporates elements of logical design into the conceptual level. Finally, we required the use of manual transformation from a conceptual into a logical data model and the results confirmed an increase in students' understanding.

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Recommender system for learning SQL using hints

Cited by 13 publications

References 30 publications

Formalizing Logic Based Rules for Skills Classification and Recommendation of Learning Materials

Formalizing Logic Based Rules for Skills Classification and Recommendation of Learning Materials

Recommendation Systems on E-Learning and Social Learning: A Systematic Review

Experimental study on the effectiveness of a teaching approach using barker or Bachman notation for conceptual database design

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