scholarly journals Mental Workload Analysis Associated with Emotional Design in E-learning Contexts: Combining EEG and Eye-Tracking Data

2021 ◽  
Author(s):  
ChenNan Wu ◽  
Yang Liu ◽  
Xiang Guo ◽  
TianShui Zhu ◽  
WeiFeng Ma
Keyword(s):  
Online Learning ◽  
Eye Tracking ◽  
Mental Workload ◽  
Physiological Data ◽  
Learning Technology ◽  
Tracking Data ◽  
Workload Analysis ◽  
Learning Contexts ◽  
Multimodal Features ◽  
E Learning

In this study, we designed a mental workload induction experiment in the context of online learning, in which EEG and eye-tracking data of participants were synchronously recorded with the aim of investigating the association between different design principles and multimodal physiological features and then applying machine-learning technology to classify mental workload states induced by those principles. This paper systematically reviews three kinds of EEG and eye-tracking features used for mental workload classification, compares the accuracy of mental workload classification between single-modal and multimodal features, modifies the mental workload index proposed by Pope et al. to monitor the variation of mental workload in E-learning contexts, and reduces the dimensions of features for more convenient use in daily life. The results of the experiment demonstrate that (1) The classification ability of wavelet power features and eye-tracking features are better than that of entropy features in E-learning contexts; (2) Multimodal physiological data can significantly improve the accuracy of mental workload classification in E-learning contexts; and (3) Correlation-based feature selection (CFS) was employed to rank all features in descending order, and when the feature dimension is reduced to 30, the optimal average classification accuracy obtained by linear-SVM is 80.2%. Furthermore, the EEG frequency bands that are highly correlated with mental workload were analyzed, and the correlation between different brain areas and mental workload discussed. All these results lay the foundation for continuous monitoring of participants’ mental workload, making it possible to endow computers with the ability to understand mental workload in E-learning contexts, which will in turn remarkably enhance participants’ learning efficiency and performance during the pandemic, and in other circumstances necessitating online learning.

scholarly journals E-learning rhetoric, creativity and innovation

2005 ◽  
Vol 13 (2) ◽  
Author(s):  
Jane Seale
Keyword(s):  
Online Learning ◽  
Policy Evaluation ◽  
Learning Technology ◽  
Current Position ◽  
The Past ◽  
E Learning ◽  
Creativity And Innovation

In this issue of ALT-J we have five papers that cover a range of policy, evaluation and development issues. The first paper, by Smith, sets the scene for the remaining papers with its focus on policy and how this may be influenced by rhetoric, and in turn may influence creativity and innovation. In ‘From flowers to palms: 40 years of policy for online learning’, Smith presents a review of learning technology-related policy over the past 40 years. The purpose of the review is to make sense of the current position in which the field finds itself, and to highlight lessons that can be learned from the implementation of previous policies.DOI: 10.1080/09687760500104039

scholarly journals Predicting Spatial Visualization Problems’ Difficulty Level from Eye-Tracking Data

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1949
Author(s):  
Xiang Li ◽  
Rabih Younes ◽  
Diana Bairaktarova ◽  
Qi Guo
Keyword(s):  
Machine Learning ◽  
Eye Tracking ◽  
Eye Movement ◽  
Spatial Visualization ◽  
Difficulty Level ◽  
Tracking Data ◽  
Multiple Choice Questions ◽  
Essential Information ◽  
E Learning ◽  
The Difference

The difficulty level of learning tasks is a concern that often needs to be considered in the teaching process. Teachers usually dynamically adjust the difficulty of exercises according to the prior knowledge and abilities of students to achieve better teaching results. In e-learning, because there is no teacher involvement, it often happens that the difficulty of the tasks is beyond the ability of the students. In attempts to solve this problem, several researchers investigated the problem-solving process by using eye-tracking data. However, although most e-learning exercises use the form of filling in blanks and choosing questions, in previous works, research focused on building cognitive models from eye-tracking data collected from flexible problem forms, which may lead to impractical results. In this paper, we build models to predict the difficulty level of spatial visualization problems from eye-tracking data collected from multiple-choice questions. We use eye-tracking and machine learning to investigate (1) the difference of eye movement among questions from different difficulty levels and (2) the possibility of predicting the difficulty level of problems from eye-tracking data. Our models resulted in an average accuracy of 87.60% on eye-tracking data of questions that the classifier has seen before and an average of 72.87% on questions that the classifier has not yet seen. The results confirmed that eye movement, especially fixation duration, contains essential information on the difficulty of the questions and it is sufficient to build machine-learning-based models to predict difficulty level.

Choosing Online Learning Communities or Collaborative Learning

2005 ◽  
pp. 90-95
Author(s):  
Daniel Teghe ◽  
Bruce Allen Knight
Keyword(s):  
Online Learning ◽  
Online Education ◽  
Computer Mediated Communication ◽  
Training Methods ◽  
Mediated Communication ◽  
Learning Contexts ◽  
Computer Mediated ◽  
Opportunities For Learning ◽  
E Learning ◽  
And Training

The adoption and innovative use of computer-mediated communication (CMC) technology can have positive outcomes for regional development (Ashford, 1999; Harris, 1999; Mitchell, 2003). Especially when it involves the use of online environments, CMC can lead to what Gillespie, Richardson, and Cornford (2001) refer to as the “death of distance,” and is likely to boost opportunities for growth in e-commerce, e-business, and e-learning in the regions. Although such growth depends on continuous learning and innovation (Rainnie, 2002), actual opportunities for learning and training can be affected by approaches to the provision of online learning that are unnecessarily rigid and inflexible. Online education and training methods that include strict participation requirements can have the effect of marginalizing and excluding those learners who cannot engage with inflexible and regimented learning contexts. This represents an important problem in regions, because of limited access to other learning contexts.

scholarly journals Feasibility Study of Massive Open Online Course (MOOC) in Supporting Self Determined Learning in Perguruan Tinggi Keagamaan Islam Negeri (PTKIN)

Compiler ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 109
Author(s):  
Sumarsono Sumarsono
Keyword(s):  
Online Learning ◽  
Quantitative Research ◽  
Learning System ◽  
Educational Institutions ◽  
Learning Technology ◽  
Face To Face ◽  
Massive Open Online Course ◽  
Digital Era ◽  
E Learning ◽  
Face To Face Learning

The learning model in the digital era has changed from traditional face-to-face learning to online learning. This causes stuttering and uncertainty for educational institutions, including the State Islamic Religious University (PTKIN), especially the readiness of lecturers. Each lecturer has different models, strategies and learning media in managing the class according to their understanding and ability in online learning. This study aims to see the readiness of PTKIN lecturers for online learning through MOOCs media with a heutagogy approach using the e-learning system at their respective universities.The quantitative research method uses 5 elements of heutagogy and 1 element of MOOCs with 52 sampling data on PTKIN lecturers.The results show that lecturers have competence and readiness in using online learning technology, but there are weaknesses in lecturers' understanding in using the heutagogy approach in learning.

scholarly journals A Simple(r) Tool For Examining Fixations

2016 ◽  
Vol 9 (4) ◽  
Author(s):  
Francesco Di Nocera ◽  
Claudio Capobianco ◽  
Simon Mastrangelo
Keyword(s):  
Eye Tracking ◽  
Open Source ◽  
Open Source Software ◽  
Time Course ◽  
Nearest Neighbor ◽  
Mental Workload ◽  
Short Paper ◽  
Tracking Data ◽  
Mental Load ◽  
Simple Tool

This short paper describes an update of A Simple Tool For Examining Fixations (ASTEF) developed for facilitating the examination of eye-tracking data and for computing a spatial statistics algorithm that has been validated as a measure of mental workload (namely, the Nearest Neighbor Index: NNI). The code is based on Matlab® 2013a and is currently distributed on the web as an open-source project. This implementation of ASTEF got rid of many functionalities included in the previous version that are not needed anymore considering the large availability of commercial and open-source software solutions for eye-tracking. That makes it very easy to compute the NNI on eye-tracking data without the hassle of learning complicated tools. The software also features an export function for creating the time series of the NNI values computed on each minute of the recording. This feature is crucial given that the spatial distribution of fixations must be used to test hypotheses about the time course of mental load.

scholarly journals Multimodal Study of the Effects of Varying Task Load Utilizing EEG, GSR and Eye-Tracking

2019 ◽  
Author(s):  
Jannis Born ◽  
Babu Ram Naidu Ramachandran ◽  
Sandra Alejandra Romero Pinto ◽  
Stefan Winkler ◽  
Rama Ratnam
Keyword(s):  
Eye Tracking ◽  
Task Performance ◽  
Mental Workload ◽  
Cognitive Task ◽  
Physiological Data ◽  
Postal Code ◽  
Subjective Data ◽  
Task Load ◽  
Minimum Number ◽  
Participant Response

AbstractObjectiveThe effect of task load on performance is investigated by simultaneously collecting multi-modal physiological data and participant response data. Periodic response to a questionnaire is also obtained. The goal is to determine combinations of modalities that best serve as predictors of task performance.ApproachA group of participants performed a computer-based visual search task mimicking postal code sorting. A five-digit number had to be assigned to one of six different non-overlapping numeric ranges. Trials were presented in blocks of progressively increasing task difficulty. The participants’ responses were collected simultaneously with 32 channels of electroencephalography (EEG) data, eye-tracking data, and Galvanic Skin Response (GSR) data. The NASA Task-Load-Index self-reporting instrument was administered at discrete time points in the experiment.Main resultsLow beta frequency EEG waves (12.5-18 Hz) were more prominent as cognitive task load increased, with most activity in frontal and parietal regions. These were accompanied by more frequent eye blinks and increased pupillary dilation. Blink duration correlated strongly with task performance. Phasic components of the GSR signal were related to cognitive workload, whereas tonic components indicated a more general state of arousal. Subjective data (NASA TLX) as reported by the participants showed an increase in frustration and mental workload. Based on one-way ANOVA, EEG and GSR provided the most reliable correlation to perceived workload level and were the most informative measures (taken together) for performance prediction.SignificanceNumerous modalities come into play during task-related activity. Many of these modalities can provide information on task performance when appropriately grouped. This study suggests that while EEG is a good predictor of task performance, additional modalities such as GSR increase the likelihood of more accurate predictions. Further, in controlled laboratory conditions, the most informative or minimum number of modalities can be isolated for monitoring in real work environments.

Efektivitas Pembelajaran Daring dengan Menggunakan E-learning Madrasah Terhadap Optimalisasi Pemahaman Matematika Siswa

2020 ◽  
Vol 5 (2) ◽  
pp. 124-136
Author(s):  
Sutini Sutini ◽  
Mohammad Mushofan ◽  
Aizza Ilmia ◽  
Anisa Dwi Yanti ◽  
Annisa Nur Rizky ◽  
...  
Keyword(s):  
Online Learning ◽  
Learning Process ◽  
Mathematics Learning ◽  
Learning System ◽  
Survey Method ◽  
Learning Technology ◽  
E Learning ◽  
The Government ◽  
Quantitative Descriptive ◽  
Teachers And Parents

During the COVID-19 pandemic, the government was requiring to be able to implement a learning system by the applicable health protocol. Based on this, the government must change the learning system from face-to-face meetings to online learning. Technology that is rapidly growing can be advantaged to fully support the online learning process so that the Ministry of Religion Affairs makes an innovation, namely e-learning madrasah media for simplifying the online learning process for all madrasah in Indonesia. This study aims to make readers know the level of effectiveness of online learning using madrasah e-learning to optimize the student understanding of mathematics. This study used a survey method that was conducted online with a quantitative descriptive research type. The results are that online mathematics learning activities using e-learning madrasah are quite efficient, considering that there are still constraints on the ownership of students' equipment and inadequate internet networks, and students are not maximal in absorbing the material provided. However, the advantages we found were the full support provided by the school, teachers, and parents for ongoing learning. Also, learning mathematics using madrasah e-learning is efficient and flexible so that students can carry out learning well.

Monitoring Activity in E-Learning

2010 ◽  
pp. 111-130 ◽  
Author(s):  
E. Mazzoni ◽  
P. Gaffuri
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Tracking Data ◽  
Specific Data ◽  
Cultural Approach ◽  
Web Environment ◽  
Learning Contexts ◽  
E Learning ◽  
Individual Actions ◽  
Monitoring Activity

In this chapter the authors will focus on the monitoring of students’ activities in e-learning contexts. They will start from a socio-cultural approach to the notion of activity, which is conceived of as a context composed by actions, which, in turn, are composed by operations. Subsequently, the authors will propose a model for monitoring activities in e-learning, which is based on two principal measures. Firstly, they will take into consideration specific data collected through Web tracking, which they will elaborate further in order to obtain indicators that do not simply express frequencies, but that measure individuals’ actions within a Web environment. Secondly, the authors will suggest a possible application of social network analysis (SNA) to Web interactions occurring in collective discussions within Web environments. In the model that the authors will present, Web tracking data are considered as indicators of individual actions, whereas SNA indices concern two levels: collective indices referring to the activity carried out by groups and individual indices referring to the role that members play in collective e-learning activities.

scholarly journals E-Learning : Implikasinya Terhadap Pelayanan Perpustakaan Perguruan Tinggi dan Peran Pustakawan

2017 ◽  
Vol 13 (1) ◽  
pp. 87
Author(s):  
Nur Etty Retno Wulandari ◽  
Eko Nugroho
Keyword(s):  
Online Learning ◽  
Teaching And Learning ◽  
Traditional Education ◽  
Learning Technology ◽  
Virtual Library ◽  
Online Journal ◽  
Technology Changes ◽  
Library Users ◽  
E Learning ◽  
Available Information

Internet, website, and online learning (e-learning) will give a great impact for the library. The library is located at the transition between electronic and printed literature, between traditional education on campus and online learning (e-learning) outside the campus. The progress of journals and electronic books also gives effect to all library users. The concept of virtual library can be a bridge between students or lectures to utilize library collections without visiting to the library. The virtual library offers the opportunity in supporting online learning (e-learning). The virtual library has the potential to change fundamental aspects of the classrooms by using the ways that can give great impact in teaching and learning. Technology changes the views of the librarians to their professions, the needs of students and faculties that will lead the change. The librarians need to be proactive in working with students to develop the collection and encourage students in thinking dependently and analyzing critically of available information. Now days, the role of librarian will change according to the changing demands of its users. In the past, the librarians only process the printed information but now they have to process the non-printed collections such as online journal. 

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