To cite:
Sharef, N. M., et. al (2020), “Learning-Analytics based Intelligent Simulator for Personalised Learning”, International Conference of Advancements in Data Science, e-Learning and Information Systems (ICADEIS’20)
- AI has huge potential to democratize education through personalized learning techniques enabled by learning analytics and adaptive technologies.
- Personalized learning aims to tailor educational content, activities and resources to individual learners based on preferences, interests, competencies and behaviors.
- Key challenges in developing truly personalized learning include limitations of data and computing power to fully understand individual learners, as well as balancing personalization with new discovery and conflicting interests of different stakeholders.
Chatbot is an Artificial Intelligence (AI) technology that serves as a digital assistant that interprets and processes users’ requests. Existing chatbot applications for teaching and learning have addressed subjects like language, and economics, but none are available to facilitate learning AI or ability to communicate in Malay language.
Therefore, CikguAIBot, a chatbot that focuses on assisting the Malay-speaking community in learning the basic concepts and algorithms of AI is developed. The purpose of the CikguAIBot is to provide an alternative to learning materials and interaction modality with the instructor. The target user of the chatbot ranges from secondary school learners to lifelong learners. CikguAIBot is deployed as a Telegram application and executable through mobile apps and web access. The completion of learning, activities and assessments of the whole content of CikguAIBot takes about one hour.
The chatbot consists of 65 intents and 7 entities, and is developed using DialogFlow, a Google-based tool. Suggestion chips and cards are used as the interaction means which allow users to navigate from one content to another. Natural language interaction is also allowed so users can chat with the chatbot. Quizzes in the form of true-false and multi-choice questions are created within each topic as a learning reinforcement purpose. Immediate feedback to answers in the quiz is also provided so the students could use the responses as self-learning. The chatbot also offers infographic, links to external resources and videos.
The document outlines 9 stages of the LORI model for evaluating educational technologies. The stages include evaluating the content quality, alignment of learning goals, ability to provide adaptive feedback, motivation of learners, design of visual and auditory presentations, ease of navigation and interface usability, accommodation of disabled learners, reusability across contexts, and compliance with international standards.
Alict evaluation of active learning materialsCorneliaBrodahl
Presentation from ALICT summer school n Kranjska Gora, Slovenia, August 5th. 2014, sponsored by Slovene Scholarship Fund EEA/NFM.
This project has been funded with support from the EEA Financial Mechanism 2009-2014 and the Norwegian Financial Mechanism 2009-2014 between the Republic of Iceland, the Principality of Liechtenstein, the Kingdom of Norway and the Republic of Slovenia. This publication (communication) is the sole responsibility of the author and in no way represents the views of the project funders.
This document discusses evaluating computer-based instruction using the multimedia authoring tool Hyper Studio. It outlines pedagogical and technical aspects to evaluate, including learning strategies, content accuracy, interactivity, navigation, and presentation. The document also describes how Hyper Studio allows flexibility and supports constructivist learning through student collaboration and presentation of projects involving various media. An evaluation strategy of peer observation is proposed to assess both the instruction and technical features of the software.
This document proposes the development of an Online Examination System (OES) for Pondicherry University. It outlines the objectives of assessing students' learning and test-taking skills through multiple choice, true/false, and other interactive question types at different difficulty levels. It describes the system architecture, roles and interfaces for administrators, instructors and students. It also provides cost estimates for content generation, development, and other project expenses, totaling 31 lakhs. Translations to other languages and future Moodle integration are mentioned.
This document evaluates the Save the Math Apples instructional software using an observation instrument. It consists of three parts:
1. Standards for pedagogical and technical aspects such as clear goals, accurate content, student control, motivation, assessment, navigation, and accessibility.
2. Description of the software including its name, screenshots, methodology as an instructional math game, and the student and teacher roles.
3. Identification of aspects to include in the observation instrument such as goals, student role, motivation, interactivity, navigation, accessibility, and user-friendliness.
- AI has huge potential to democratize education through personalized learning techniques enabled by learning analytics and adaptive technologies.
- Personalized learning aims to tailor educational content, activities and resources to individual learners based on preferences, interests, competencies and behaviors.
- Key challenges in developing truly personalized learning include limitations of data and computing power to fully understand individual learners, as well as balancing personalization with new discovery and conflicting interests of different stakeholders.
Chatbot is an Artificial Intelligence (AI) technology that serves as a digital assistant that interprets and processes users’ requests. Existing chatbot applications for teaching and learning have addressed subjects like language, and economics, but none are available to facilitate learning AI or ability to communicate in Malay language.
Therefore, CikguAIBot, a chatbot that focuses on assisting the Malay-speaking community in learning the basic concepts and algorithms of AI is developed. The purpose of the CikguAIBot is to provide an alternative to learning materials and interaction modality with the instructor. The target user of the chatbot ranges from secondary school learners to lifelong learners. CikguAIBot is deployed as a Telegram application and executable through mobile apps and web access. The completion of learning, activities and assessments of the whole content of CikguAIBot takes about one hour.
The chatbot consists of 65 intents and 7 entities, and is developed using DialogFlow, a Google-based tool. Suggestion chips and cards are used as the interaction means which allow users to navigate from one content to another. Natural language interaction is also allowed so users can chat with the chatbot. Quizzes in the form of true-false and multi-choice questions are created within each topic as a learning reinforcement purpose. Immediate feedback to answers in the quiz is also provided so the students could use the responses as self-learning. The chatbot also offers infographic, links to external resources and videos.
The document outlines 9 stages of the LORI model for evaluating educational technologies. The stages include evaluating the content quality, alignment of learning goals, ability to provide adaptive feedback, motivation of learners, design of visual and auditory presentations, ease of navigation and interface usability, accommodation of disabled learners, reusability across contexts, and compliance with international standards.
Alict evaluation of active learning materialsCorneliaBrodahl
Presentation from ALICT summer school n Kranjska Gora, Slovenia, August 5th. 2014, sponsored by Slovene Scholarship Fund EEA/NFM.
This project has been funded with support from the EEA Financial Mechanism 2009-2014 and the Norwegian Financial Mechanism 2009-2014 between the Republic of Iceland, the Principality of Liechtenstein, the Kingdom of Norway and the Republic of Slovenia. This publication (communication) is the sole responsibility of the author and in no way represents the views of the project funders.
This document discusses evaluating computer-based instruction using the multimedia authoring tool Hyper Studio. It outlines pedagogical and technical aspects to evaluate, including learning strategies, content accuracy, interactivity, navigation, and presentation. The document also describes how Hyper Studio allows flexibility and supports constructivist learning through student collaboration and presentation of projects involving various media. An evaluation strategy of peer observation is proposed to assess both the instruction and technical features of the software.
This document proposes the development of an Online Examination System (OES) for Pondicherry University. It outlines the objectives of assessing students' learning and test-taking skills through multiple choice, true/false, and other interactive question types at different difficulty levels. It describes the system architecture, roles and interfaces for administrators, instructors and students. It also provides cost estimates for content generation, development, and other project expenses, totaling 31 lakhs. Translations to other languages and future Moodle integration are mentioned.
This document evaluates the Save the Math Apples instructional software using an observation instrument. It consists of three parts:
1. Standards for pedagogical and technical aspects such as clear goals, accurate content, student control, motivation, assessment, navigation, and accessibility.
2. Description of the software including its name, screenshots, methodology as an instructional math game, and the student and teacher roles.
3. Identification of aspects to include in the observation instrument such as goals, student role, motivation, interactivity, navigation, accessibility, and user-friendliness.
The document discusses content chunking in e-learning. Content chunking involves splitting information into small, easily digestible pieces. This helps learners understand information more easily. There is a five-step process for comprehending content before chunking: gathering inputs, analyzing content, setting learning objectives, researching and summarizing, and creating a course map. Content should be chunked at both the course level, by creating a detailed outline, and screen level, with one learning point per screen. Effective chunking is key to developing an effective e-learning course.
This professional development module focused on 5 principles for online teaching: 1) using student data to plan instruction, 2) incorporating self-reflection, 3) assessment strategies, 4) effective learning strategies, and 5) communication tools. Participants learned how to interpret student data to individualize instruction, researched different assessment models, and discovered new communication tools to engage virtual learners. Participants were provided a binder to organize research into data analysis, assessments, self-reflection tools, and communication portfolios to build upon for ongoing professional growth.
Computer-based training (CBT) is a type of education where students learn through computer programs rather than from a teacher. The computer takes on the role of instructor by managing learning processes, monitoring progress, and assessing results. Common forms of CBT include tutorials, demonstrations, and simulations. While CBT has benefits like flexibility and individualization, it also has drawbacks such as high costs, technical limitations, and lack of social interaction. Effective CBT requires evaluating programs based on their technology, content, and pedagogical approach.
Computer-assisted instruction (CAI) refers to using computers to provide drill-and-practice, tutorials, or simulations to students, while computer-managed instruction (CMI) uses computers to track student progress and provide individualized learning objectives, resources, and assessments. CAI involves direct interaction between students and educational software, and can take forms like drill-and-practice, tutorials, games, simulations, discovery, and problem-solving. CMI allows instructors to manage instruction for individual students and choose objectives and activities based on their needs. Both approaches provide benefits like self-paced learning and immediate feedback but also have limitations like over-reliance on multimedia or lack of infrastructure.
Computer-based instruction involves students interacting with a computer as a key part of learning. It can include simulations, tutorials, practice, instructional games, and problem solving. Some advantages are that it is highly interactive, requires less time than traditional methods, and requires active participation from students. However, limitations include students getting distracted by other computer uses, the time needed to develop materials, and the costs of equipment and software. Not all subjects can be assisted by computer-based instruction.
This document discusses computer assisted instruction (CAI) in education. It defines CAI as an interactive instructional technique using computers to present material and monitor learning. CAI allows individualized self-paced instruction. It describes different types of CAI including drill and practice, tutorials, games, and simulations. The document also outlines the characteristics, features, uses, role of teachers, merits, and limitations of CAI. It concludes that while CAI has benefits for students, teachers are still needed to support learning and address limitations.
This document discusses computer-based instruction (CBI), including its categories, characteristics, applications in education, advantages, limitations, and research findings. CBI is defined as using computers to deliver instruction and includes drill and practice, tutorials, simulations, instructional games, and problem solving. Research shows CBI can improve performance over traditional methods, take less time, and positively impact student attitudes. Effective integration and evaluation of software are also covered.
AN AUTOMATED MULTIPLE-CHOICE QUESTION GENERATION USING NATURAL LANGUAGE PROCE...kevig
Automatic multiple-choice question generation (MCQG) is a useful yet challenging task in Natural Language
Processing (NLP). It is the task of automatic generation of correct and relevant questions from textual data.
Despite its usefulness, manually creating sizeable, meaningful and relevant questions is a time-consuming
and challenging task for teachers. In this paper, we present an NLP-based system for automatic MCQG for
Computer-Based Testing Examination (CBTE).We used NLP technique to extract keywords that are
important words in a given lesson material. To validate that the system is not perverse, five lesson materials
were used to check the effectiveness and efficiency of the system. The manually extracted keywords by the
teacher were compared to the auto-generated keywords and the result shows that the system was capable of
extracting keywords from lesson materials in setting examinable questions. This outcome is presented in a
user-friendly interface for easy accessibility.
CAI can be used effectively for drill and practice activities to reinforce learning through repetition of basic skills and knowledge. It works best for topics like vocabulary, math facts, and sciences. Drill and practice software provides immediate feedback on answers and performance summaries. While drill and practice are useful for 20-30 minutes, CAI should also incorporate tutorial software to teach new content beyond exercises. Tutorial software provides comprehensive information and allows teachers to ask follow-up questions to stimulate deeper learning. CAI can positively impact learning when used for remediation, review, enrichment, and cooperative group activities.
Computers are a familiar sight in classrooms in the 21st century, and technology has been used to streamline many educational tasks. CAL started in the 1950s and 1960s mainly in USA. Term often used interchangeably with Computer-Based Instruction (CBI), Web Based Instruction (WBI), Computer-Assisted Learning (CAL), Computer-Enriched Instruction (CEI), and Web Based Training (WBT). Logo project was the first CAL system that was based on a specific learning approach.
The project aims at developing an intelligent tutoring system, to be applied in open source learning environments, able to monitor, track, analyze and give formative assessment and feedback loop to students within the learning environment, and give inputs to tutors and teachers involved in distance learning to better their role during the process of learning. The software will be developed in java thus could be easily implemented and re-used in most of the common free platforms for eLearning.
The document provides a template for a long-range lesson planner that teachers can use to plan units of instruction. The template includes sections for standards, learning indicators, summative assessments, objectives, formative assessments, learning activities, text resources, technology resources, cooperative groupings, content-based reading and writing, hands-on experiences, individualized instruction, material resources, and other planning considerations. Teachers can use this template to map out all aspects of a instructional unit over multiple lessons.
CBT refers to computer-based training, which is a type of education that uses computers to deliver instructional content. With CBT, students learn through training programs executed on a computer, CD-ROM, or online. CBT is similar to other acronyms like CAI, CMI, CBI, CAL, and CAT that all refer to computer-assisted or computer-managed forms of learning and instruction. CBT can be used for formal, non-formal, and informal learning and is created based on principles of behaviorism, cognitivism, and constructivism learning theories. Common forms of CBT include demonstration, tutorial, and simulation.
Need analysis for the development of a microcontroller instructional module p...journalBEEI
In the era of the IR 4.0, the use of information technology among school students is widespread but students are not proficient in computer programming. To compete in the digital world, students need to be exposed to computer programming in order to produce computer programming experts. Integrating computer programming into the school curriculum can improve students literacy of computer programming but adequate computer programming skill among teachers are quite limited. Therefore, the development of microcontroller instructional teaching module which could address this problem is needed. This development aims to develop the module using design and developmental research (DDR) approach. Need Analysis phase in DDR is discussed in this article. The phase consists of identifying the level of knowledge, attitudes and practices of teachers about microcontroller and to obtain the views and opinions of the teachers on the developmental needs of microcontroller teaching modules. The type of microcontroller and the programming language to be used in the microcontroller module also identified.The results of this study are important to ensure that the design and development of an instructional module for microcontroller education are implemented and have a positive impact on increasing the programming literacy level among secondary school children
The readiness of academic staff at South Valley University to develop and imp...Alaa Sadik
The study aimed to evaluate the readiness of academic staff at South Valley University in Egypt to develop and implement e-learning. It assessed staff competencies, experiences, and attitudes regarding e-learning. A survey was administered to 233 staff members to measure these three dimensions. Results found that staff had positive attitudes towards e-learning but lacked technical competencies, training, and experience developing e-learning. The study recommends that the university provide training programs and technical support to help staff overcome barriers to e-learning adoption.
The document provides an overview of a 5-day teacher training workshop on implementing e-learning. It discusses instructional design principles and models, e-learning modalities, open source software, building an online learning platform, and evaluating online content. The objectives are to define common terms and processes for e-learning, build understanding of instructional design, and guide teachers in designing an online course web board and publishing web pages.
Here are the key points about the role of teachers in CAI/CAL:
- Guide and facilitate students' learning. Monitor their progress.
- Design and develop appropriate CAL modules/programs based on curriculum.
- Train students in using computers and CAL programs effectively.
- Provide support and clarify doubts when students face difficulties in understanding concepts.
- Evaluate and improve existing CAL programs based on students' feedback. Develop new programs.
- Use CAI/CAL as a supplement rather than replacement for traditional teaching. Optimize use of both methods.
- Act as facilitators and guides rather than only information providers during CAI/CAL sessions.
So in summary, teachers play an important role
E-Learning Student Assistance Model for the First Computer Programming CourseIJITE
The document presents an e-learning student assistance model called c-Learn for novice computer programming students. c-Learn was developed to address low passing rates in introductory programming courses by providing tutoring, assessment, and backtracking guidance. It was tested on 11 students who used c-Learn for 2.5 hours, showing improved exam scores compared to their initial midterm. c-Learn uses color-coded syntax, interactive exercises, and compiler feedback. It requires achieving a 70% threshold in each section before advancing, or backs students to relevant earlier sections if below the threshold. The study found c-Learn improved students' marks and increased the standard deviation, indicating it positively impacted learning for students with different capabilities.
Path to Success for Every Student
India's First AI-based Diagnostic Assessment to
Identify Gaps, Help students learn and Measure Growth
all in one easy system for Academic and Skills
The world of eLearning has revolutionized the way people learn and acquire new skills. With the rapid growth of technology and internet, learners have access to a adaptive learning plethora of online resources and platforms to enhance their knowledge and expertise.
This document outlines the Masters in Personnel Management (MPM) program at the University of Pune Faculty of Management. The two-year, full-time MPM program uses a credit and grading system and aims to develop students' understanding of human resource management concepts, techniques, and practices. The program consists of full and half credit courses, a research mini project, field work, and a six credit Summer Internship Project. Students are evaluated through university exams accounting for 50% of marks and continuous concurrent evaluation making up the other 50% through components like case studies, assignments, and presentations.
This document discusses evaluating the effectiveness of educational technology in the classroom. It provides an evaluation cycle that includes evaluating technology before, during, and after instruction. The document also discusses evaluating software programs based on content, documentation/support, ability levels, assessment, technical quality, and ease of use. Several types of student assessments are mentioned, including traditional, alternative, project-based, and portfolio assessments. Checklists, rating scales, and rubrics are presented as tools for developing evaluations.
The document discusses content chunking in e-learning. Content chunking involves splitting information into small, easily digestible pieces. This helps learners understand information more easily. There is a five-step process for comprehending content before chunking: gathering inputs, analyzing content, setting learning objectives, researching and summarizing, and creating a course map. Content should be chunked at both the course level, by creating a detailed outline, and screen level, with one learning point per screen. Effective chunking is key to developing an effective e-learning course.
This professional development module focused on 5 principles for online teaching: 1) using student data to plan instruction, 2) incorporating self-reflection, 3) assessment strategies, 4) effective learning strategies, and 5) communication tools. Participants learned how to interpret student data to individualize instruction, researched different assessment models, and discovered new communication tools to engage virtual learners. Participants were provided a binder to organize research into data analysis, assessments, self-reflection tools, and communication portfolios to build upon for ongoing professional growth.
Computer-based training (CBT) is a type of education where students learn through computer programs rather than from a teacher. The computer takes on the role of instructor by managing learning processes, monitoring progress, and assessing results. Common forms of CBT include tutorials, demonstrations, and simulations. While CBT has benefits like flexibility and individualization, it also has drawbacks such as high costs, technical limitations, and lack of social interaction. Effective CBT requires evaluating programs based on their technology, content, and pedagogical approach.
Computer-assisted instruction (CAI) refers to using computers to provide drill-and-practice, tutorials, or simulations to students, while computer-managed instruction (CMI) uses computers to track student progress and provide individualized learning objectives, resources, and assessments. CAI involves direct interaction between students and educational software, and can take forms like drill-and-practice, tutorials, games, simulations, discovery, and problem-solving. CMI allows instructors to manage instruction for individual students and choose objectives and activities based on their needs. Both approaches provide benefits like self-paced learning and immediate feedback but also have limitations like over-reliance on multimedia or lack of infrastructure.
Computer-based instruction involves students interacting with a computer as a key part of learning. It can include simulations, tutorials, practice, instructional games, and problem solving. Some advantages are that it is highly interactive, requires less time than traditional methods, and requires active participation from students. However, limitations include students getting distracted by other computer uses, the time needed to develop materials, and the costs of equipment and software. Not all subjects can be assisted by computer-based instruction.
This document discusses computer assisted instruction (CAI) in education. It defines CAI as an interactive instructional technique using computers to present material and monitor learning. CAI allows individualized self-paced instruction. It describes different types of CAI including drill and practice, tutorials, games, and simulations. The document also outlines the characteristics, features, uses, role of teachers, merits, and limitations of CAI. It concludes that while CAI has benefits for students, teachers are still needed to support learning and address limitations.
This document discusses computer-based instruction (CBI), including its categories, characteristics, applications in education, advantages, limitations, and research findings. CBI is defined as using computers to deliver instruction and includes drill and practice, tutorials, simulations, instructional games, and problem solving. Research shows CBI can improve performance over traditional methods, take less time, and positively impact student attitudes. Effective integration and evaluation of software are also covered.
AN AUTOMATED MULTIPLE-CHOICE QUESTION GENERATION USING NATURAL LANGUAGE PROCE...kevig
Automatic multiple-choice question generation (MCQG) is a useful yet challenging task in Natural Language
Processing (NLP). It is the task of automatic generation of correct and relevant questions from textual data.
Despite its usefulness, manually creating sizeable, meaningful and relevant questions is a time-consuming
and challenging task for teachers. In this paper, we present an NLP-based system for automatic MCQG for
Computer-Based Testing Examination (CBTE).We used NLP technique to extract keywords that are
important words in a given lesson material. To validate that the system is not perverse, five lesson materials
were used to check the effectiveness and efficiency of the system. The manually extracted keywords by the
teacher were compared to the auto-generated keywords and the result shows that the system was capable of
extracting keywords from lesson materials in setting examinable questions. This outcome is presented in a
user-friendly interface for easy accessibility.
CAI can be used effectively for drill and practice activities to reinforce learning through repetition of basic skills and knowledge. It works best for topics like vocabulary, math facts, and sciences. Drill and practice software provides immediate feedback on answers and performance summaries. While drill and practice are useful for 20-30 minutes, CAI should also incorporate tutorial software to teach new content beyond exercises. Tutorial software provides comprehensive information and allows teachers to ask follow-up questions to stimulate deeper learning. CAI can positively impact learning when used for remediation, review, enrichment, and cooperative group activities.
Computers are a familiar sight in classrooms in the 21st century, and technology has been used to streamline many educational tasks. CAL started in the 1950s and 1960s mainly in USA. Term often used interchangeably with Computer-Based Instruction (CBI), Web Based Instruction (WBI), Computer-Assisted Learning (CAL), Computer-Enriched Instruction (CEI), and Web Based Training (WBT). Logo project was the first CAL system that was based on a specific learning approach.
The project aims at developing an intelligent tutoring system, to be applied in open source learning environments, able to monitor, track, analyze and give formative assessment and feedback loop to students within the learning environment, and give inputs to tutors and teachers involved in distance learning to better their role during the process of learning. The software will be developed in java thus could be easily implemented and re-used in most of the common free platforms for eLearning.
The document provides a template for a long-range lesson planner that teachers can use to plan units of instruction. The template includes sections for standards, learning indicators, summative assessments, objectives, formative assessments, learning activities, text resources, technology resources, cooperative groupings, content-based reading and writing, hands-on experiences, individualized instruction, material resources, and other planning considerations. Teachers can use this template to map out all aspects of a instructional unit over multiple lessons.
CBT refers to computer-based training, which is a type of education that uses computers to deliver instructional content. With CBT, students learn through training programs executed on a computer, CD-ROM, or online. CBT is similar to other acronyms like CAI, CMI, CBI, CAL, and CAT that all refer to computer-assisted or computer-managed forms of learning and instruction. CBT can be used for formal, non-formal, and informal learning and is created based on principles of behaviorism, cognitivism, and constructivism learning theories. Common forms of CBT include demonstration, tutorial, and simulation.
Need analysis for the development of a microcontroller instructional module p...journalBEEI
In the era of the IR 4.0, the use of information technology among school students is widespread but students are not proficient in computer programming. To compete in the digital world, students need to be exposed to computer programming in order to produce computer programming experts. Integrating computer programming into the school curriculum can improve students literacy of computer programming but adequate computer programming skill among teachers are quite limited. Therefore, the development of microcontroller instructional teaching module which could address this problem is needed. This development aims to develop the module using design and developmental research (DDR) approach. Need Analysis phase in DDR is discussed in this article. The phase consists of identifying the level of knowledge, attitudes and practices of teachers about microcontroller and to obtain the views and opinions of the teachers on the developmental needs of microcontroller teaching modules. The type of microcontroller and the programming language to be used in the microcontroller module also identified.The results of this study are important to ensure that the design and development of an instructional module for microcontroller education are implemented and have a positive impact on increasing the programming literacy level among secondary school children
The readiness of academic staff at South Valley University to develop and imp...Alaa Sadik
The study aimed to evaluate the readiness of academic staff at South Valley University in Egypt to develop and implement e-learning. It assessed staff competencies, experiences, and attitudes regarding e-learning. A survey was administered to 233 staff members to measure these three dimensions. Results found that staff had positive attitudes towards e-learning but lacked technical competencies, training, and experience developing e-learning. The study recommends that the university provide training programs and technical support to help staff overcome barriers to e-learning adoption.
The document provides an overview of a 5-day teacher training workshop on implementing e-learning. It discusses instructional design principles and models, e-learning modalities, open source software, building an online learning platform, and evaluating online content. The objectives are to define common terms and processes for e-learning, build understanding of instructional design, and guide teachers in designing an online course web board and publishing web pages.
Here are the key points about the role of teachers in CAI/CAL:
- Guide and facilitate students' learning. Monitor their progress.
- Design and develop appropriate CAL modules/programs based on curriculum.
- Train students in using computers and CAL programs effectively.
- Provide support and clarify doubts when students face difficulties in understanding concepts.
- Evaluate and improve existing CAL programs based on students' feedback. Develop new programs.
- Use CAI/CAL as a supplement rather than replacement for traditional teaching. Optimize use of both methods.
- Act as facilitators and guides rather than only information providers during CAI/CAL sessions.
So in summary, teachers play an important role
E-Learning Student Assistance Model for the First Computer Programming CourseIJITE
The document presents an e-learning student assistance model called c-Learn for novice computer programming students. c-Learn was developed to address low passing rates in introductory programming courses by providing tutoring, assessment, and backtracking guidance. It was tested on 11 students who used c-Learn for 2.5 hours, showing improved exam scores compared to their initial midterm. c-Learn uses color-coded syntax, interactive exercises, and compiler feedback. It requires achieving a 70% threshold in each section before advancing, or backs students to relevant earlier sections if below the threshold. The study found c-Learn improved students' marks and increased the standard deviation, indicating it positively impacted learning for students with different capabilities.
Path to Success for Every Student
India's First AI-based Diagnostic Assessment to
Identify Gaps, Help students learn and Measure Growth
all in one easy system for Academic and Skills
The world of eLearning has revolutionized the way people learn and acquire new skills. With the rapid growth of technology and internet, learners have access to a adaptive learning plethora of online resources and platforms to enhance their knowledge and expertise.
This document outlines the Masters in Personnel Management (MPM) program at the University of Pune Faculty of Management. The two-year, full-time MPM program uses a credit and grading system and aims to develop students' understanding of human resource management concepts, techniques, and practices. The program consists of full and half credit courses, a research mini project, field work, and a six credit Summer Internship Project. Students are evaluated through university exams accounting for 50% of marks and continuous concurrent evaluation making up the other 50% through components like case studies, assignments, and presentations.
This document discusses evaluating the effectiveness of educational technology in the classroom. It provides an evaluation cycle that includes evaluating technology before, during, and after instruction. The document also discusses evaluating software programs based on content, documentation/support, ability levels, assessment, technical quality, and ease of use. Several types of student assessments are mentioned, including traditional, alternative, project-based, and portfolio assessments. Checklists, rating scales, and rubrics are presented as tools for developing evaluations.
GaETC 2004 - LTTS: Online Professional Development for Technology IntegrationMichael Barbour
Barbour, M. K., Bleich, L., & Orrill C. (2004, February). LTTS: Online professional development for technology integration. Paper presented at the annual Georgia Educational Technology Conference, Macon, GA.
Technology Based Assessment Tools TEC 536 AA (1).pptxAlaaAlian
This document discusses different tools that teachers can use for formative and summative assessments, including Quizlet for recall questions, Blooket for skills and concepts, Edpuzzle for strategic thinking, Buncee for extended thinking, and Nearpod for peer review and self-assessment. Each tool is described in 1-2 sentences and their appropriate grade levels are provided. Standards from the International Society for Technology in Education are included for each tool.
This document discusses instructional design basics and principles. It defines instructional design as the systematic development of instruction to ensure quality learning based on analysis of needs and goals. The key aspects covered are:
- Applying principles to develop comprehensive courses and measurable objectives
- Determining appropriate activities, assessments and evaluations to enhance learning
- Ensuring alignment between goals, objectives, strategies and assessments
- Following an instructional design process of analysis, design, development, implementation and evaluation
- Designing for active and effective learning through various strategies
This document provides guidance on developing learning outcomes. It begins by outlining the intended learning outcomes of the workshop, which are to develop outcomes adhering to the SMART principles, critique existing outcomes, and demonstrate constructive alignment. It then defines curriculum and outlines the topics to be covered, including learning outcomes, constructive alignment, and consolidation. The document provides details on writing outcomes focusing on what students can do, guidelines for effective outcomes using Bloom's taxonomy and level descriptors, and the importance of alignment between outcomes, teaching strategies, and assessment. It includes examples and activities for writing and evaluating outcomes to ensure they are specific, measurable, attainable, relevant, and targeted.
MyFoundationsLab is an online program that assesses students' skills in reading, writing, and math through diagnostic tests. It then creates a personalized learning path for each student focused on the areas they need to improve. Students work through modules and topics in each subject area, completing activities and assessments to demonstrate their mastery of the material. Educators can track each student's progress and make adjustments to the course content and mastery settings. MyFoundationsLab aims to help students strengthen their college and career readiness skills.
AI In Student Performance: Important Roles, Tools, Benefits, Challenges | Fu...Future Education Magazine
Here are 5 roles of AI in student performance: 1. Personalized Learning 2. Automation of Administrative Tasks 3. Immediate Feedback 4. Predictive Analytics 5. Enhanced Data Analysis
The document provides guidance on designing modular or part-time learning programs. It outlines steps to:
1) Analyze learner needs and program parameters by defining purpose, outcomes, target group characteristics and benchmark standards.
2) Generate content and structure options using learning principles and styles.
3) Develop the program content, structure, resources, timeframes and costs.
4) Review and finalize the program for approval and implementation.
Convergence of Pedagogies and Technologies- A case study of MS-CIT by Mr. Viv...SNDTWU
This document discusses the convergence of pedagogies and technologies used in Maharashtra State Certificate in Information Technology (MS-CIT). It describes the infrastructure and software used at learning centers, including the ERA eLearning platform. It outlines a typical learner's journey, from admission to academics. It also discusses MKCL's educational approach, focusing on work-centric and experiential learning principles. Finally, it covers the various eAssessment methods used to evaluate learners, including objective tests, portfolios, and an assignment management system.
The document discusses developing a learning analytics company that analyzes student work on a continuous basis to provide personalized feedback and learning content tailored to each student's strengths and weaknesses. It outlines how the company would aggregate performance data across subjects, concepts and time to generate personalized learning records, feedback and recommendations to help students improve. The theoretical basis and desired service specifications are also described.
Developing an Information System for E-Portfolio Based Knowledge Generation a...ePortfolios Australia
Developing an Information System for E-Portfolio Based Knowledge Generation and Sharing in Teacher Education
Mariamma Mathew, Thomas Uzhuvath, Tony Cherian and Aswathy G.
Peet Memorial Training College, Mavelikara, Kerala State, India
Abstract
This project, which aims to develop a professional portfolio for teacher educators and student teachers, is in its budding stage. The focus is to develop a Learning Management System with many of the social networking features.Student teachers can upload products including My Teaching Philosophy, Reflective Journal, Lesson Plans, Teaching Video and Photos in addition to detailed personal and academic profiles,.Every product is uploaded with a reflective note and there is a provision for comments and feedback. A major feature is to make performance assessment strategies as an integral part of the portfolio system. The self,peer, and mentor assessmentsare carried out using rubrics. Login to the system is also allowed for educational institutions, employers and guests and the public. It is expected that the system works as an effective tool for engaging student teachers and teacher educators to create and share a pool of pedagogical knowledge.
This document discusses developing an instructional strategy. It covers selecting a delivery system, sequencing content, determining learning components for different learners and outcomes, using constructivist strategies, grouping students, and choosing media. The delivery system describes how instruction is provided, such as online, in-person, or blended. Content is sequenced logically and clustered into manageable chunks. Learning components include getting attention, stating objectives, and providing feedback. Strategies should consider learner maturity and abilities as well as the type of learning outcome.
Evaluating the efficacy of an online class.ppteugrissom
The document discusses evaluating the efficacy of online courses. It outlines complaints students had about disorganization, inconsistency, and lack of clarity. To address these issues, the authors developed questions to consider how online courses should be designed and what elements are needed for quality. Their research identified that instructional design, communication and learning experiences, and assessment of student achievement are key to ensuring academic rigor and a meaningful learning experience. The conclusion emphasizes that instructional design is paramount and should incorporate instructor presence, timely feedback, and tools to meet learning objectives.
The document outlines the process of program design, including defining program design, listing characteristics of successful programmers, and elements of an effective program design such as program title, objectives, contents, duration, topics, and facilitators. It also discusses methods of training during the program, factors to consider in design such as covering all contents and using various training methods, and the steps involved in program design from the preparatory to writing to validation phases. Finally, it lists advantages like improving education quality and bringing individualized instruction, and disadvantages such as losing student interest from too many errors.
The document discusses developing learning outcomes for outcome-based education. It emphasizes that learning outcomes should be specific, measurable, achievable, relevant and timed. Learning outcomes can be defined at different levels, including program objectives, program outcomes, course outcomes and weekly outcomes. Developing learning outcomes involves mapping them to learning activities and assessing their achievement. Stakeholders such as students, academics and employers should be involved in preparing learning outcomes. Periodic review and improvement of learning outcomes is also discussed.
Designing and Conducting Formative EvaluationAngel Jones
The document discusses formative evaluation, which involves gathering feedback from learners to improve instructional materials. It describes a three-stage process for conducting formative evaluation: 1) One-to-one evaluation identifies obvious errors; 2) Small group evaluation tests effectiveness of changes and learners' ability to use materials independently; 3) Field trials determine if changes are effective and if materials can be used as intended. The goal is to refine materials through quantitative and qualitative data collection so they achieve desired learning outcomes when implemented.
Similar to Learning analytics based intelligent simulator for personalised learning slide (20)
This talk was delivered for the National Defense University of Malaysia (Universiti Pertahanan Malaysia), Malaysia, in their academic staffs induction course program, delivered on 9th August 2023. The title is Regenerating learning experience with AI.
Struggle to success: How generative ai can transform your university experience?Nurfadhlina Mohd Sharef
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2. Educators should redesign activities and assessments to focus on skills like critical thinking, communication, and experiential learning rather than just facts. Assessments should evaluate creation of artifacts rather than past problems.
3. While AI tools have limitations and can generate incorrect information, they can engage students in productive struggle if used to supplement rather than replace student effort. Universities must prepare students
This webinar is conducted by the Centre for Academic Development and Leadership Excellence (CADe-Lead) on 14th April 2023. Here is the link to the event page https://cadelead.upm.edu.my/kandungan/olcpd2023_14_apr_ada_apa_dengan_chatgpt_tanyalah_dr_fadh-72294
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This talk is organised by HELWA ABIM to create awareness on big data and artificial intelligence. Delivered by Nurfadhlina Mohd Sharef on 5th November 2020
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To cite: Sharef, N.M., Mustapha, A., Azmi, M.N., Nordin, R., (2020), "Basketball Players Performance Analytic as Experiential Learning Approach in Teaching Undergraduate Data Science Course", International Conference on Advancement in Data Science, E-learning and Information Systems (ICADEIS 2020).
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Khairudin, N., Sharef, N. M., Mustapha, N., Noah, S A. M., (2018), "Enhancing Multi-Aspect Collaborative Filtering for Personalized Recommendation", 2018 Fourth International Conference on Information Retrieval and Knowledge Management (CAMP18), Kota Kinabalu
Aspect Extraction Performance With Common Pattern of Dependency Relation in ...Nurfadhlina Mohd Sharef
A. S., Shafie, Sharef, N. M., Murad, M. A. A., Azman, A., (2018), "Aspect Extraction Performance With Common Pattern of Dependency Relation in Multi Aspect Sentiment Analysis", 2018 Fourth International Conference on Information Retrieval and Knowledge Management (CAMP18), Kota Kinabalu, in press.
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a system called natural language interface which transforms user's natural language question into SPARQL query
find related papers here https://sites.google.com/site/fadhlinams81/publication
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3. Personalised learning through meaningful experiential
learning analytic
1. Instructor must determine suitable
pedagogies that could optimize
meaningful learning experience.
2. The choice and preparation of learning
materials should be optimized as well.
3. Instructor has good competencies and
familiarity with the course.
4. The instructor should also be informed on
the learners’ profile and able to identify
the students’ learning needs.
1. Instruction in which the pace of learning
and the instructional approach are
optimized for the needs of each learner
where the learning objectives,
instructional approaches, and
instructional content (and its sequencing)
may all vary based on learner needs.
2. Learning activities are made available
that are meaningful and relevant to
learners, driven by their interests and
often self-initiated.
Characteristics Actions
5. Why is it important to conduct Learning Analytics?
6. Intelligent Simulator for Personalised Learning (ISPerL)
Benefits and purpose of ISPerL for meaningful learning analytic can be
further described as follows:
a. Plan a personalized lesson
i. Plan upcoming lesson and get prediction on the satisfaction
score
ii. View current course summary and past lesson
information
b. Conduct adaptive teaching
i. View students heart rate
ii. View participation and engagement score
c. Learning scaffolding
i. Analyse students’ achievement by assessment types
ii. Analyse students’ achievement by program outcomes
iii. Analyse students’ participation and engagement
iv. Analyse students’ satisfaction
There are two chatbots developed in ISPerL.
The purpose of the first chatbot is to
provide alternative to learning materials
and interaction modality with the
instructor. The chatbot is designed in
Bahasa Melayu, which is the national
language in Malaysia. The target user of the
chatbot ranges from secondary school
learners to lifelong learners. The second
chatbot aims to provide customer service
related to academic program’s admission
enquiries.
7. Which algorithms and features best predict the
end of term academic performance of students
by comparing different classificationalgorithms
and pre-processing techniques and whether or
not academicperformance can be predicted in
the earlier weeks using these features and
theselected algorithm
7
10. Features
Students Really
Expect from
Learning
Analytics
● time spent online
● collaborative learning with friends and colleagues
● learning recommendation for successful course completion
● prefer self/independent learning rather than conventional
classroom setting
● timeline showing current status and goal
● time needed to complete a task or read a text
● prompts for self-assessments
● further learning recommendations
● comparison with fellow students
● considering the students personal calendar for appropriate
learning recommendations
● newsfeed with relevant news matching the learning content
● revision of former learning content
● feedback for assignments
● reminder for deadlines
● term scheduler, recommending relevant courses
11. Descriptive Learning Analytic Diagnostic Learning Analytic
Personalised Learning Facilitation through Meaningful Learning
Experience Analysis
Predictive Learning Analytic
Prescriptive Learning Analytic
● Lesson records visualization and alert on low
attendance
● Assessments record visualization and alert on low
assessment achievements
● PO achievements records visualization and alert
on low PO achievements
● Statistics on learning materials, learning activities,
satisfaction records and reaction in each lesson
● Correlate assessment achievement with
demographic profile, attendance,
participation, engagement and satisfaction
● Correlate PO achievement with
demographic profile, attendance,
participation, engagement and satisfaction
● Predict grade based on attendance,
participation, engagement and satisfaction
● Predict satisfaction based on materials,
activities and student demography
● Prescribe remedial actions based on
gap in students attendance
participation, engagement, satisfaction
and achievements
● Prescribe remedial actions based on
predicted grade performance
12. Lesson
Satisfaction
Learning AnalyticReaction to Lesson
Learning Materials
Assessment Records
Descriptive Diagnostic
Predictive Prescriptive
Chatbot
Student
Lecturer and
Administrator
Intelligent Simulator for
Personalised Learning
(ISPerL) model)
Version
1
13. ProfilingLearning preferences
Learning competency
Learning behavior
- System
participation log
- Heart rate
Learning satisfaction
Learning Personalization Analytics
Descriptive
(preferences, satisfaction, competency,
achievement)
Diagnostic-learning plan
adaptability
(preferences-behavior,
satisfaction-achievement)
Predictive-learning plan
recommendation
(performance, satisfaction)
Prescriptive-Adaptive learning
plan
(performance, satisfaction)
Assessment records
Learning Materials
Learning dashboard
Learning engagement
Learning achievement
Satisfaction prediction
Performance prediction
Learning competency
Customization
Model of Intelligent Simulator for Personalised Learning (ISPerL)
Version
2
14. For Learners For Instructors
- Pre-lesson execution
- Planning of lesson
- Prediction of satisfaction score
- Prediction of grade
- During lesson execution
- Average heart rate of class
- View heart rate of each student
- Participation and engagement by each
students
- Participation and engagement alert of
class
- Post-lesson execution
- Analysis of participation, engagement,
heart rate, satisfaction rating and
achievement
ISPerL Features
For Instructors and Administrators
- Descriptive analytic of course,
lesson and student info
- Diagnostic analytic on course
performance by gender, PO and
assessment type
- Comparative analytic on course
performance across gender, PO
and assessment type, groups and
semesters
- Predictive analytic on students
and course performance
(assessment , PO for current and
cross group , semester)
- View course info
- View lesson plan
- View graph of heart beat vs
ideal heart beat
- Assign rating for content,
delivery, engagement
- View self-standing vs average
participation in the course
- View self-standing vs average
achievement in the course
- Execute chatbot
15. Features:
1. View
- Course Info
- Course Assessment
- Course PO
- Comparison between
semesters
- Analysis of heart rate
1. Plan a new lesson & view
lessons for current
semester
2. Get prediction of content,
delivery and engagement
satisfaction
Intelligent Simulator for Personalised Learning (ISPerL)
16. Descriptive Learning Analytic of Learning Outcome distribution
- Comparing grade distribution
across groups within the same
semester
- Comparing marks distribution
by PO across groups within the
same semester
- Comparing marks distribution
by PO across gender and groups
within the same semester
- Comparing marks distribution
by PO across gender, groups
and semester
- Comparing marks distribution
by PO across gender, groups
and semester of each grade
Showcase: https://public.tableau.com/profile/nurfadhlina.mohd.sharef#!/vizhome/LearningAnalytic-Course1/Story-
LearningAnalytic?publish=yes
20. POWERPOINT TEMPLATEWhirlWind | Email : example@example.com | Web : www.example.com
This is a sample text, Insert your desired text here this is a sample text.
Pilot 2
22. Guru AI Bot- teaches the basics of
artificial intelligence, in Malay language.
Modifying current chatbot based on input
from pilot study - 50%
Development of questionnaires - 100%
User study setup - 50%
FSKTMBot - customer service
chatbot that entertains admission
inquiries.
Development of chatbot - 100%
Development of questionnaires - 100%
User study setup - 40%
1. What? A virtual assistant for the Artificial Intelligence (AI)
subject
2. Scope? Basic information on AI
3. Who? Anyone who likes to learn about the basic of AI
4. Language? Malay
1. What? A virtual assistant for ADMISSION inquiries into Faculty
of Computer Science and Information Technology, UPM.
2. Scope? Information (Programme, Requirement, Fees, Contact
Us)
3. Who? Future and current students that seeking for basic
information of the FCSIT
4. Language? English
24. A customer service chatbot that
entertains admission inquiries.
FSKTMBot
1. What? A virtual assistant for ADMISSION inquiries into
Faculty of Computer Science and Information Technology,
UPM.
2. Scope? Information (Programme, Requirement, Fees,
Contact Us)
3. Who? Future and current students that seeking for basic
information of the FCSIT
4. How? Rule-based Natural Language Processing using
DialogFlow framework
5. Language? English
25. Thank you from us..
To cite:
Sharef, N. M., et. al (2020), “Learning-Analytics based Intelligent
Simulator for Personalised Learning”, International Conference of
Advancements in Data Science, e-Learning and Information Systems
(ICADEIS’20)
Please visit our website https://qrgo.page.link/7EEdp