Abstract:

Online learning has become an essential component of modern education, offering learners easy access to a wealth of educational resources. However, this abundance of information can sometimes overwhelm learners, making it challenging for them to focus on key concepts. Semantic networks, by providing guided navigation of conceptual relations, have the potential to overcome these challenges by allowing learners to follow a logical path from one concept to another, thereby facilitating access to relevant information and enhancing the effectiveness of online learning.

The primary research inquiry addressed in this article is: How do semantic networks improve learner performance through the facilitation of guided navigation of conceptual relations in online learning systems?

The objectives of this study are as follows:
• To examine the influence of semantic networks on guided navigation of conceptual relations in online learning systems.
• To assess the extent to which guided navigation of conceptual relations enhances learners' access to pertinent information.
• To identify how guided navigation of conceptual relations addresses knowledge gaps among learners.
• To investigate how guided navigation of conceptual relations strengthens learners' comprehension of studied concepts.

To address the research question and achieve the stated objectives, we will adopt a mixed-method research approach, incorporating quantitative and qualitative methods:
• Data Collection: Data will be collected from several online learning systems that utilize semantic networks to represent knowledge. The collected data will include learner interactions with the semantic network, such as link clicks, time spent on each concept, etc.
• Quantitative Analysis: Quantitative methods will be employed to analyze the collected data. We will assess information retention rates, average time spent on concepts, and learners' progress to evaluate the effectiveness of guided navigation of conceptual relations.
• Surveys and Qualitative Interviews: Surveys will be conducted among learners to gather their opinions and perceptions regarding the use of semantic networks in their learning process. Qualitative interviews will also be conducted with teachers and course designers to obtain their insights into the impact of semantic networks on learning.
• Comparison with Traditional Methods: To assess the effectiveness of guided navigation of conceptual relations, we will compare the performance of learners using semantic networks with those using more traditional online learning methods, such as static content lists.
• Results Analysis: Quantitative and qualitative data will be analyzed jointly to provide a comprehensive overview of the effects of semantic networks on guided navigation of conceptual relations. The results will be interpreted to address the research question and achieve the objectives.

By combining quantitative and qualitative approaches, this study aims to provide a comprehensive analysis of the impact of semantic networks on learner performance through guided navigation of conceptual relations in online learning systems. The obtained results will contribute to improving our understanding of the effective use of semantic networks to optimize online learning and provide a more enriching educational experience for learners.

Keywords:

Semantic networks, learner performance, guided navigation, conceptual relations.