How Does Prior Knowledge Impact Students’ Online Learning Behaviors?

2011 ◽  
Vol 1 (4) ◽  
pp. 1-18 ◽  
Author(s):  
Kirsten R. Butcher ◽  
Tamara Sumner
Keyword(s):  
Online Learning ◽  
Prior Knowledge ◽  
Domain Knowledge ◽  
Learning Task ◽  
Factual Knowledge ◽  
Student Interactions ◽  
Digital Resources ◽  
Web Based ◽  
Learning Behaviors ◽  
The Impact

This study explored the impact of prior domain knowledge on students’ strategies and use of digital resources during a Web-based learning task. Domain knowledge was measured using pre- and posttests of factual knowledge and knowledge application. Students utilized an age- and topic-relevant collection of 796 Web resources drawn from an existing educational digital library to revise essays that they had written prior to the online learning task. Following essay revision, participants self-reported their strategies for improving their essays. Screen-capture software was used to record all student interactions with Web-based resources and all modifications to their essays. Analyses examined the relationship between different levels of students’ prior knowledge and online learning behaviors, self-reported strategies, and learning outcomes. Findings demonstrated that higher levels of factual prior knowledge were associated with deeper learning and stronger use of digital resources, but that higher levels of deep prior knowledge were associated with less frequent use of online content and fewer deep revisions. These results suggest that factual knowledge can serve as a useful knowledge base during self-directed, online learning tasks, but deeper prior knowledge may lead novice learners to adopt suboptimal processes and behaviors.

How Does Prior Knowledge Impact Students’ Online Learning Behaviors?

2013 ◽  
pp. 97-115
Author(s):  
Kirsten R. Butcher ◽  
Tamara Sumner
Keyword(s):  
Online Learning ◽  
Prior Knowledge ◽  
Domain Knowledge ◽  
Learning Task ◽  
Factual Knowledge ◽  
Student Interactions ◽  
Digital Resources ◽  
Web Based ◽  
Learning Behaviors ◽  
Frequent Use

This study explored the impact of prior domain knowledge on students’ strategies and use of digital resources during a Web-based learning task. Domain knowledge was measured using pre- and posttests of factual knowledge and knowledge application. Students utilized an age- and topic-relevant collection of 796 Web resources drawn from an existing educational digital library to revise essays that they had written prior to the online learning task. Following essay revision, participants self-reported their strategies for improving their essays. Screen-capture software was used to record all student interactions with Web-based resources and all modifications to their essays. Analyses examined the relationship between different levels of students’ prior knowledge and online learning behaviors, self-reported strategies, and learning outcomes. Findings demonstrated that higher levels of factual prior knowledge were associated with deeper learning and stronger use of digital resources, but that higher levels of deep prior knowledge were associated with less frequent use of online content and fewer deep revisions. These results suggest that factual knowledge can serve as a useful knowledge base during self-directed, online learning tasks, but deeper prior knowledge may lead novice learners to adopt suboptimal processes and behaviors.

Encouraging and Increasing Student Engagement and Participation in an Online Classroom

2016 ◽  
pp. 426-447
Author(s):  
Kathryn Woods
Keyword(s):  
Online Learning ◽  
Student Engagement ◽  
Learning Environment ◽  
Prior Knowledge ◽  
Learning Environments ◽  
Online Courses ◽  
Traditional Classroom ◽  
Online Classroom ◽  
Online Learning Environments ◽  
The Impact

Advances in technology have increased opportunities for students to participate in online courses. While some instructors are beginning their careers teaching only online courses, others are discovering a need to teach sections of courses online after they have enjoyed a long career teaching in a traditional classroom. In either situation, it is important for instructors to recognize that students in online learning environments require the use of different strategies for encouraging engagement and participation in class. In this chapter, the author describes the challenges that students and instructors face specifically in the online learning environment as well as strategies for success, including how to maximize the impact of students' experiences and prior knowledge, using multiple platforms to deliver information, discouraging procrastination, setting clear expectations, encouraging individuality, capitalizing on diversity, and providing and utilizing helpful resources.

scholarly journals Implementasi Pendekatan Saintifik pada Pembelajaran Daring Selama Masa Pandemi Covid-19 di Lembaga Pendidikan Dasar

AS-SABIQUN ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 45-63
Author(s):  
Ahmad Izzuddin
Keyword(s):  
Online Learning ◽  
Basic Education ◽  
Parental Supervision ◽  
Learning Technology ◽  
Learning Approaches ◽  
Student Interactions ◽  
Scientific Approach ◽  
Asking Questions ◽  
Online Methods ◽  
The Impact

The impact of the Covid-19 pandemic is felt at all levels of education, from elementary to higher education. The existence of this pandemic has become a challenge for educators to innovate in developing and implementing lesson plans that have been prepared previously. One of the learning approaches used is the scientific approach. This approach trains students to learn with the scientific method through the process of observing, asking questions, gathering information, experimenting, associating and communicating the material they are learning. This is where the ability of a teacher is required to be creative in integrating the steps of the scientific approach with online methods. During the past year, the implementation of a scientific approach in online learning during the Covid-19 pandemic has been carried out in basic education institutions with quite good results. Some of the advantages of the scientific approach using online learning include (1) the dependence of students on educators is slightly reduced because learning is carried out more at home through the network (online) (2) the flexibility of time and place to take the steps of the scientific approach to be a separate experience for students (3 ) train students to use learning technology from an early age. The weaknesses of online learning include (1) internet signal/connection is not very stable (2) teacher and student interactions cannot interact directly (3) still lack of facilities and infrastructure in the implementation of online learning (4) inadequate parental supervision This causes students to often lose focus in learning.

scholarly journals Utilizing peer interactions to promote learning through a web-based peer assessment system

2009 ◽  
Vol 34 (2) ◽  
Author(s):  
Lan Li ◽  
Allen L. Steckelberg ◽  
Sribhagyam Srinivasan
Keyword(s):  
Student Perceptions ◽  
Instructional Strategy ◽  
Peer Interactions ◽  
Peer Assessment ◽  
Peer Pressure ◽  
Assessment System ◽  
Time On Task ◽  
Student Interactions ◽  
Web Based ◽  
The Impact

Peer assessment is an instructional strategy in which students evaluate each other’s performance for the purpose of improving learning. Despite its accepted use in higher education, researchers and educators have reported concerns such as students’ time on task, the impact of peer pressure on the accuracy of marking, and students’ lack of ability to make critical judgments about peers’ work. This study explored student perceptions of a web-based peer assessment system. Findings conclude that web-based peer assessment can be effective in minimizing peer pressure, reducing management workload, stimulating student interactions, and enhancing student understanding of marking criteria and critical assessment skills. Résumé : L’évaluation par les pairs est une stratégie pédagogique au cours de laquelle l’étudiant évalue la performance de l’autre dans un but d’amélioration de l’apprentissage. Malgré son usage répondu aux études supérieures, les chercheurs et les enseignants ont mentionné certaines préoccupations, notamment en ce qui a trait au temps que les étudiants consacrent à cette tâche, à l’impact de la pression des pairs sur la justesse de l’évaluation, ainsi qu’à l’inaptitude des étudiants à poser un jugement critique sur le travail de leurs pairs. La présente étude explore les perceptions des étudiants à l’égard d’un système d’évaluation en ligne par les pairs. Nos résultats nous permettent de conclure que l’évaluation en ligne par les pairs peut constituer un moyen efficace de réduire la pression des pairs, de diminuer le travail de gestion, de stimuler les interactions entre étudiants et d’améliorer la compréhension des critères d’évaluation par les étudiants ainsi que leurs compétences d’évaluation critique.

scholarly journals Finding the optimal Bayesian network given a constraint graph

2017 ◽  
Vol 3 ◽  
pp. e122 ◽  
Author(s):  
Jacob M. Schreiber ◽  
William S. Noble
Keyword(s):  
Bayesian Network ◽  
Prior Knowledge ◽  
Domain Knowledge ◽  
Structure Learning ◽  
Learning Task ◽  
Computational Time ◽  
Constraint Graph ◽  
Intuitive Method ◽  
Time Required ◽  
Optimal Graph

Despite recent algorithmic improvements, learning the optimal structure of a Bayesian network from data is typically infeasible past a few dozen variables. Fortunately, domain knowledge can frequently be exploited to achieve dramatic computational savings, and in many cases domain knowledge can even make structure learning tractable. Several methods have previously been described for representing this type of structural prior knowledge, including global orderings, super-structures, and constraint rules. While super-structures and constraint rules are flexible in terms of what prior knowledge they can encode, they achieve savings in memory and computational time simply by avoiding considering invalid graphs. We introduce the concept of a “constraint graph” as an intuitive method for incorporating rich prior knowledge into the structure learning task. We describe how this graph can be used to reduce the memory cost and computational time required to find the optimal graph subject to the encoded constraints, beyond merely eliminating invalid graphs. In particular, we show that a constraint graph can break the structure learning task into independent subproblems even in the presence of cyclic prior knowledge. These subproblems are well suited to being solved in parallel on a single machine or distributed across many machines without excessive communication cost.

scholarly journals Finding the optimal bayesian network given a constraint graph

2017 ◽  
Author(s):  
Jacob M Schreiber ◽  
William S Noble
Keyword(s):  
Bayesian Network ◽  
Prior Knowledge ◽  
Domain Knowledge ◽  
Structure Learning ◽  
Learning Task ◽  
Computational Time ◽  
Constraint Graph ◽  
Intuitive Method ◽  
Time Required ◽  
Optimal Graph

Despite recent algorithmic improvements, learning the optimal structure of a Bayesian network from data is typically infeasible past a few dozen variables. Fortunately, domain knowledge can frequently be exploited to achieve dramatic computational savings, and in many cases domain knowledge can even make structure learning tractable. Several methods have previously been described for representing this type of structural prior knowledge, including global orderings, super-structures, and constraint rules. While super-structures and constraint rules are flexible in terms of what prior knowledge they can encode, they achieve savings in memory and computational time simply by avoiding considering invalid graphs. We introduce the concept of a "constraint graph" as an intuitive method for incorporating rich prior knowledge into the structure learning task. We describe how this graph can be used to reduce the memory cost and computational time required to find the optimal graph subject to the encoded constraints, beyond merely eliminating invalid graphs. In particular, we show that a constraint graph can break the structure learning task into independent subproblems even in the presence of cyclic prior knowledge. These subproblems are well suited to being solved in parallel on a single machine or distributed across many machines without excessive communication cost.

Culture, Interaction, and Online Learning

2011 ◽  
pp. 485-491
Author(s):  
Janet Toland ◽  
Jonathan Frank ◽  
Karen D. Schenk
Keyword(s):  
Distance Education ◽  
Online Learning ◽  
South Pacific ◽  
The South ◽  
Global Knowledge ◽  
Student Body ◽  
Web Based ◽  
Knowledge Based ◽  
Diverse Student Body ◽  
The Impact

Technological innovation and the development of global knowledge-based economies are presenting higher education institutions throughout the developing world with both opportunities and challenges. The development of distance education has particular relevance for remote and widely distributed locations. The scattered geography of the South Pacific has produced immense variations in culture amongst a relatively low population base. This makes the South Pacific an ideal region in which to explore the impact of cultural differences on online learning. Online learning offers the developing countries of the South Pacific the chance to open up access to even the most distantly located students. This research evaluates the effectiveness of e-mail as a mechanism for encouraging Web-based interaction among students in two distance education institutions with a culturally and geographically diverse student body.

Encouraging and Increasing Student Engagement and Participation in an Online Classroom

2016 ◽  
pp. 1335-1357
Author(s):  
Kathryn Woods
Keyword(s):  
Online Learning ◽  
Student Engagement ◽  
Learning Environment ◽  
Prior Knowledge ◽  
Learning Environments ◽  
Online Courses ◽  
Traditional Classroom ◽  
Online Classroom ◽  
Online Learning Environments ◽  
The Impact

Advances in technology have increased opportunities for students to participate in online courses. While some instructors are beginning their careers teaching only online courses, others are discovering a need to teach sections of courses online after they have enjoyed a long career teaching in a traditional classroom. In either situation, it is important for instructors to recognize that students in online learning environments require the use of different strategies for encouraging engagement and participation in class. In this chapter, the author describes the challenges that students and instructors face specifically in the online learning environment as well as strategies for success, including how to maximize the impact of students' experiences and prior knowledge, using multiple platforms to deliver information, discouraging procrastination, setting clear expectations, encouraging individuality, capitalizing on diversity, and providing and utilizing helpful resources.

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