Work and Community-based Learning: From the Classroom to the Outside World

Community Based Learning (CBL) is a pedagogical approach that is based on the premise that the most profound learning often comes from experience that is supported by guidance, context-providing, foundational knowledge, and intellectual analysis. The opportunity for students to bring thoughtful knowledge and ideas based on personal observation and social interaction to a course’s themes and scholarly arguments brings depth to the learning experience for individuals and to the content of the course. (Swarthmore College | http://tinyurl.com/jrhpf4x)

Community-based learning refers to a wide variety of instructional methods and programs that educators use to connect what is being taught in schools to their surrounding communities, including local institutions, history, literature, cultural heritage, and natural environments.

All the community-based learning activities are student-centered, which minimizes the effect of conventional pedagogical method and equips students with chances to interact with the outside world using their available and applicable knowledge. From philanthropic activities such as volunteerism, community services to work-based ones like internships, practicum, students are allowed to use acquired skills and immediate knowledge to solve real-world problems, preparing them better for the future career path and contributing to addressing the needs of the community, as articulated by the community itself via school channels. As a result, students can develop practical and useful skills to cope with a drastically changing environment, understand and reflect themselves more frequently to build clearer goals for future, and be able to become compassionate leaders.

Work and Community-based Learning should be considered as the most appropriate metric to measure and evaluate students' competence, skills and understanding in different contexts beyond the confinement of quizzes, tests, exams or punctuation. Also, this form of teaching and learning gives a glimpse into their personality, responsibility, tolerance and many more characteristics that would be of great use when being released into labor market.

Interestingly speaking, many people are attempting to build online community to perform community learning. A simplest form to register for an online group that shares the same interest as you and is teaching and learning on your subject. One example I found is Ashley Fox's community, Wealth Without Wall Street built on the website called Mighty Pro. Ashley uses her knowledge and story as a former Wall Street trader to bring financial literacy to the other 99% of people who don't have access to Wall Street-level knowledge. (https://www.mightynetworks.com/resources/community-based-learning). Another awesome project is Be My Eyes, an online app allows any volunteers around the world to connect with and assist the blind and low-vision users in everyday situations. This form of service learning can be a good starting point of people of all age to access into the philanthropic activity while remaining online.

• Vee Phan

Adaptive learning is an approach that utilizes artificial intelligence (AI) and data analytics to tailor learning pathways, content, and assessments based on individual learner interactions. This technology dynamically modifies the difficulty level, presentation style, and pacing of educational materials to optimize comprehension and engagement. Unlike traditional one-size-fits-all education models, adaptive learning personalizes the experience, ensuring that each learner receives targeted support and challenges at their appropriate level.

Example of Adaptive Learning in Practice
A great example of adaptive learning in practice is Knewton Alta, an AI-driven learning platform that provides personalized math and science instruction. By continuously analyzing a student's responses and interactions, Knewton Alta adapts the learning materials to match their skill level, filling knowledge gaps and reinforcing concepts where needed. This approach ensures a more efficient and engaging learning experience.

How Does Adaptive Learning Fit into Ubiquitous Learning?
Ubiquitous learning thrives on accessibility, flexibility, and personalization, making adaptive learning technologies a perfect fit. These systems use real-time analytics to provide feedback, suggest resources, and adapt assessments based on a learner’s progress. Whether integrated into LMS platforms, MOOCs, mobile learning applications, or blended learning environments, adaptive learning enhances student engagement and retention by making learning truly individualized.

Benefits of Adaptive Learning Technologies:
• Personalized Learning Paths: Learners receive customized instruction tailored to their strengths and weaknesses.
• Real-Time Feedback: Instant feedback helps learners understand mistakes and improve efficiently.
• Data-Driven Insights: Educators can analyze learning patterns and refine instructional strategies.
• Scalability: Large groups of learners can receive individualized learning experiences without the need for constant human intervention.


A Concept in Need of Definition: Microlearning in Adaptive Learning Ecosystems
While microlearning—bite-sized, focused educational content—has gained traction, its integration within adaptive learning remains underexplored. How can adaptive systems effectively structure microlearning experiences to maximize retention and engagement? Exploring this intersection could provide new insights into the future of personalized, ubiquitous learning.

For more information, don't hesitate to send me.

• Manal Emara

Adaptive learning is an approach that utilizes artificial intelligence (AI) and data analytics to tailor learning pathways, content, and assessments based on individual learner interactions. This technology dynamically modifies the difficulty level, presentation style, and pacing of educational materials to optimize comprehension and engagement. Unlike traditional one-size-fits-all education models, adaptive learning personalizes the experience, ensuring that each learner receives targeted support and challenges at their appropriate level.

Example of Adaptive Learning in Practice
A great example of adaptive learning in practice is Knewton Alta, an AI-driven learning platform that provides personalized math and science instruction. By continuously analyzing a student's responses and interactions, Knewton Alta adapts the learning materials to match their skill level, filling knowledge gaps and reinforcing concepts where needed. This approach ensures a more efficient and engaging learning experience.

How Does Adaptive Learning Fit into Ubiquitous Learning?
Ubiquitous learning thrives on accessibility, flexibility, and personalization, making adaptive learning technologies a perfect fit. These systems use real-time analytics to provide feedback, suggest resources, and adapt assessments based on a learner’s progress. Whether integrated into LMS platforms, MOOCs, mobile learning applications, or blended learning environments, adaptive learning enhances student engagement and retention by making learning truly individualized.

Benefits of Adaptive Learning Technologies:
• Personalized Learning Paths: Learners receive customized instruction tailored to their strengths and weaknesses.
• Real-Time Feedback: Instant feedback helps learners understand mistakes and improve efficiently.
• Data-Driven Insights: Educators can analyze learning patterns and refine instructional strategies.
• Scalability: Large groups of learners can receive individualized learning experiences without the need for constant human intervention.


A Concept in Need of Definition: Microlearning in Adaptive Learning Ecosystems
While microlearning—bite-sized, focused educational content—has gained traction, its integration within adaptive learning remains underexplored. How can adaptive systems effectively structure microlearning experiences to maximize retention and engagement? Exploring this intersection could provide new insights into the future of personalized, ubiquitous learning.

For more information, don't hesitate to send me.

• Manal Emara

Adaptive learning is an approach that utilizes artificial intelligence (AI) and data analytics to tailor learning pathways, content, and assessments based on individual learner interactions. This technology dynamically modifies the difficulty level, presentation style, and pacing of educational materials to optimize comprehension and engagement. Unlike traditional one-size-fits-all education models, adaptive learning personalizes the experience, ensuring that each learner receives targeted support and challenges at their appropriate level.

Example of Adaptive Learning in Practice
A great example of adaptive learning in practice is Knewton Alta, an AI-driven learning platform that provides personalized math and science instruction. By continuously analyzing a student's responses and interactions, Knewton Alta adapts the learning materials to match their skill level, filling knowledge gaps and reinforcing concepts where needed. This approach ensures a more efficient and engaging learning experience.

How Does Adaptive Learning Fit into Ubiquitous Learning?
Ubiquitous learning thrives on accessibility, flexibility, and personalization, making adaptive learning technologies a perfect fit. These systems use real-time analytics to provide feedback, suggest resources, and adapt assessments based on a learner’s progress. Whether integrated into LMS platforms, MOOCs, mobile learning applications, or blended learning environments, adaptive learning enhances student engagement and retention by making learning truly individualized.

Benefits of Adaptive Learning Technologies:
• Personalized Learning Paths: Learners receive customized instruction tailored to their strengths and weaknesses.
• Real-Time Feedback: Instant feedback helps learners understand mistakes and improve efficiently.
• Data-Driven Insights: Educators can analyze learning patterns and refine instructional strategies.
• Scalability: Large groups of learners can receive individualized learning experiences without the need for constant human intervention.


A Concept in Need of Definition: Microlearning in Adaptive Learning Ecosystems
While microlearning—bite-sized, focused educational content—has gained traction, its integration within adaptive learning remains underexplored. How can adaptive systems effectively structure microlearning experiences to maximize retention and engagement? Exploring this intersection could provide new insights into the future of personalized, ubiquitous learning.

For more information, don't hesitate to send me.

• Manal Emara

Adaptive learning is an approach that utilizes artificial intelligence (AI) and data analytics to tailor learning pathways, content, and assessments based on individual learner interactions. This technology dynamically modifies the difficulty level, presentation style, and pacing of educational materials to optimize comprehension and engagement. Unlike traditional one-size-fits-all education models, adaptive learning personalizes the experience, ensuring that each learner receives targeted support and challenges at their appropriate level.

Example of Adaptive Learning in Practice
A great example of adaptive learning in practice is Knewton Alta, an AI-driven learning platform that provides personalized math and science instruction. By continuously analyzing a student's responses and interactions, Knewton Alta adapts the learning materials to match their skill level, filling knowledge gaps and reinforcing concepts where needed. This approach ensures a more efficient and engaging learning experience.

How Does Adaptive Learning Fit into Ubiquitous Learning?
Ubiquitous learning thrives on accessibility, flexibility, and personalization, making adaptive learning technologies a perfect fit. These systems use real-time analytics to provide feedback, suggest resources, and adapt assessments based on a learner’s progress. Whether integrated into LMS platforms, MOOCs, mobile learning applications, or blended learning environments, adaptive learning enhances student engagement and retention by making learning truly individualized.

Benefits of Adaptive Learning Technologies:
• Personalized Learning Paths: Learners receive customized instruction tailored to their strengths and weaknesses.
• Real-Time Feedback: Instant feedback helps learners understand mistakes and improve efficiently.
• Data-Driven Insights: Educators can analyze learning patterns and refine instructional strategies.
• Scalability: Large groups of learners can receive individualized learning experiences without the need for constant human intervention.


A Concept in Need of Definition: Microlearning in Adaptive Learning Ecosystems
While microlearning—bite-sized, focused educational content—has gained traction, its integration within adaptive learning remains underexplored. How can adaptive systems effectively structure microlearning experiences to maximize retention and engagement? Exploring this intersection could provide new insights into the future of personalized, ubiquitous learning.

For more information, don't hesitate to send me.

• Manal Emara

Adaptive learning is an approach that utilizes artificial intelligence (AI) and data analytics to tailor learning pathways, content, and assessments based on individual learner interactions. This technology dynamically modifies the difficulty level, presentation style, and pacing of educational materials to optimize comprehension and engagement. Unlike traditional one-size-fits-all education models, adaptive learning personalizes the experience, ensuring that each learner receives targeted support and challenges at their appropriate level.

Example of Adaptive Learning in Practice
A great example of adaptive learning in practice is Knewton Alta, an AI-driven learning platform that provides personalized math and science instruction. By continuously analyzing a student's responses and interactions, Knewton Alta adapts the learning materials to match their skill level, filling knowledge gaps and reinforcing concepts where needed. This approach ensures a more efficient and engaging learning experience.

How Does Adaptive Learning Fit into Ubiquitous Learning?
Ubiquitous learning thrives on accessibility, flexibility, and personalization, making adaptive learning technologies a perfect fit. These systems use real-time analytics to provide feedback, suggest resources, and adapt assessments based on a learner’s progress. Whether integrated into LMS platforms, MOOCs, mobile learning applications, or blended learning environments, adaptive learning enhances student engagement and retention by making learning truly individualized.

Benefits of Adaptive Learning Technologies:
• Personalized Learning Paths: Learners receive customized instruction tailored to their strengths and weaknesses.
• Real-Time Feedback: Instant feedback helps learners understand mistakes and improve efficiently.
• Data-Driven Insights: Educators can analyze learning patterns and refine instructional strategies.
• Scalability: Large groups of learners can receive individualized learning experiences without the need for constant human intervention.


A Concept in Need of Definition: Microlearning in Adaptive Learning Ecosystems
While microlearning—bite-sized, focused educational content—has gained traction, its integration within adaptive learning remains underexplored. How can adaptive systems effectively structure microlearning experiences to maximize retention and engagement? Exploring this intersection could provide new insights into the future of personalized, ubiquitous learning.

For more information, don't hesitate to send me.

• Manal Emara

https://www.coursera.org/learn/elearning/peer/uyi4o/essential-peer-reviewed-update-1/discussions/threads/pLs7qfUFEe-JfAr_0M44ZQ

• مها آل صالح

Ubiquitous Learning Concept: Networked Learning

Networked learning is a ubiquitous learning concept that emphasizes the connection between learners, instructors, and resources through technology-enabled networks. This approach allows for collaborative learning experiences that are not limited by physical proximity, setting up learners to engage in meaningful discourse and knowledge construction across various digital platforms.

One practical example of networked learning is the use of Massive Open Online Courses (MOOCs), where participants from around the world engage in discussions, share insights, and collaborate on assignments through discussion forums, video lectures, and peer assessments. MOOCs, such as those offered by Coursera or edX, provide an excellent model of networked learning, demonstrating how learners can connect across geographical and cultural boundaries to enhance their educational experiences.

Another example is the use of professional learning communities (PLCs) on platforms like LinkedIn Learning or Google Classroom, where educators and professionals share best practices, discuss industry trends, and collaborate on projects. These communities exemplify how networked learning facilitates continuous professional development and knowledge-sharing in real time.
To explore more about networked learning, check out these resources:
• Siemens, G. (2005). Connectivism: A Learning Theory for the Digital Age. Retrieved from http://www.elearnspace.org/Articles/connectivism.htm
• Coursera. (n.d.). Massive Open Online Courses (MOOCs). Retrieved from https://www.coursera.org

• Teresa Crowther Miss T

إنترنت الأشياء (IoT)
إنترنت الأشياء (IoT) هو مفهوم حديث يربط الأجهزة الذكية بشبكة الإنترنت، مما يسمح لها بالتواصل وتبادل البيانات دون تدخل بشري مباشر. يعتمد هذا النظام على تقنيات مثل المستشعرات، والذكاء الاصطناعي، والحوسبة السحابية، مما يجعل الحياة أكثر كفاءة وذكاءً.
مكونات إنترنت الأشياء
يتكون إنترنت الأشياء من عدة عناصر أساسية، تشمل:
1. الأجهزة الذكية: مثل الهواتف، وأجهزة الاستشعار، والكاميرات، والمعدات الصناعية.
2. شبكات الاتصال: مثل Wi-Fi، وBluetooth، و5G، التي تتيح نقل البيانات بين الأجهزة.
3. البرمجيات والمنصات السحابية: التي تقوم بمعالجة البيانات وتحليلها لتقديم استجابات ذكية.
تطبيقات إنترنت الأشياء
يُستخدم IoT في العديد من المجالات، ومنها:
• المنازل الذكية: حيث يمكن التحكم في الإضاءة، والتدفئة، والأجهزة المنزلية عن بُعد.
• الرعاية الصحية: من خلال الأجهزة القابلة للارتداء التي تراقب صحة المرضى وتنبه الأطباء عند الحاجة.
• المدن الذكية: التي تشمل أنظمة المرور الذكية، وإدارة الطاقة، وتحسين خدمات الأمن.
• الصناعة والزراعة: إذ يساعد IoT في تحسين الإنتاجية عبر أتمتة العمليات وجمع البيانات الدقيقة.
التحديات والمخاطر
رغم الفوائد العديدة، يواجه إنترنت الأشياء تحديات، مثل:
• الأمان والخصوصية: إذ يمكن استغلال البيانات المخزنة بطرق غير قانونية.
• التكلفة العالية: لإنشاء وصيانة البنية التحتية المطلوبة.
• التوافق بين الأجهزة: حيث تحتاج الشركات إلى تطوير معايير موحدة لتسهيل الاتصال بين الأجهزة المختلفة.

• Abdullah Al Harthi

جزاكم كل الخير

• Manal Emara

Blended Learning, also known as flipped classroom, hybrid learning, or mixed learning, is an instructional approach that combines traditional in-person teaching and face-to-face interaction with digital media and online learning. This approach integrates personal interactions such as workshops or classroom sessions with self-paced e-learning modules, virtual training, or digital resources, offering a flexible and comprehensive educational experience. The hybrid approach allows learners to engage with materials both collaboratively and independently, making it highly effective in adapting to diverse learning preferences and enhancing knowledge retention.
Types of Blended Learning
Blended Learning Models
Here are the five most common models of blended learning:
1. Flipped Classroom Model
In this model, traditional teaching is reversed. Learners first encounter the instructional content outside the classroom, typically through video lectures, readings, or online modules. Class time is then dedicated to active learning, discussions, group projects, and activities that reinforce the pre-learned material.
o This model facilitates more personalized and interactive learning during in-person sessions and offers flexibility for students to learn at their own pace.
2. Face-to-Face Driver Model
This model closely resembles traditional classroom training, with most instruction taking place in a physical classroom under the guidance of an instructor.
o It provides personalized support to learners struggling with new concepts or falling behind in the curriculum.
3. Rotation Model
Learners rotate between different learning methods, such as face-to-face instruction, online activities, group discussions, and independent study. These rotations can follow a set schedule (daily or weekly) or be based on the learners’ progress.
o This model offers flexibility and caters to different learning styles, allowing learners to engage in the method that works best for them at a given time.
4. Flex Model
This model gives learners significant autonomy and control over their learning path. It combines online learning with in-person support when needed. With the use of adaptive learning platforms, learners can choose when and where to access digital content and resources, making it suitable for self-directed learning.
o Instructors provide assistance as required to help learners progress.
5. Enhanced Virtual Model
This model primarily relies on online learning with periodic in-person sessions. Most of the learning occurs in a virtual environment, but learners attend physical classes or workshops at set intervals for hands-on activities, assessments, or collaborative projects.
Benefits of Blended Learning
The following are the benefits of a blended learning approach for employee development strategies within organizations:
• Combining Theory and Practice:
Enables employees to engage with theoretical concepts through e-learning modules and apply that knowledge in practical contexts, such as workshops or simulations.
• Reducing Costs and Improving ROI:
Reduces expenses by minimizing the need for physical spaces, travel, and printed materials. Digital modules can be reused or updated at a lower cost.
• Facilitating Corporate Training Feedback:
Digital platforms allow for immediate feedback and assessments, making it easier for trainers to monitor progress and identify knowledge gaps.
• Enabling Self-Paced Learning:
Offers employees the flexibility to complete e-learning components on their own schedule, ensuring they absorb the material without feeling rushed.
• Enhancing Collaboration and Group Learning:
Encourages interaction through elements such as forums, group projects, and live sessions, promoting teamwork and knowledge exchange among employees.
• Improving Knowledge Retention:
The combination of self-directed learning and interactive activities enhances information retention. Learners can revisit digital content when needed, while practical experiences deepen understanding.
How to Create a Blended Learning Program
To create an effective blended learning program, follow these steps:
1. Define Training Goals:
Clearly identify objectives using SMART principles. Ensure the goals are Specific, Measurable, Achievable, Relevant, and Time-bound.
2. Choose the Appropriate Blended Learning Model:
Select a model based on the nature of the objectives, target audience, and available resources.
3. Select the Optimal Delivery Methods:
Use methods such as e-learning modules, live virtual training, workshops, mobile learning, and simulations.
4. Invest in Blended Learning Tools:
o Learning Management Systems (LMS)
o Digital Adoption Platforms (DAP)
o Hands-on Training Environments
5. Evaluate Effectiveness:
Use assessments, tests, and reviews to measure outcomes.
6. Collect Feedback and Improve the Program:
Gather participant feedback to refine and adapt the program to meet changing needs.
References:
https://whatfix.com/blog/blended-learning-types-benefits-examples/ https://youtu.be/4nkXLL7ajEQ?si=X1dfoSWWpAOIBFjE https://youtu.be/kwA2LY4P1Fc?si=FUODEnDYU87sou-T https://youtu.be/OEmaK_ZzB24?si=CHIhlzqZ30aZ89w9

• Inas Ahmed Inas Ahmed

thanks

• Manal Emara

thanks

• Manal Emara

Thank you, Professor Enas, for this cognitive enrichment. I agree with you that blended learning combines traditional face-to-face education with online education, providing a flexible and diverse educational experience for students.

• Abdullah Al Harthi