Regarding alternative forms of assessment, an example is project-based assessment. In this approach, students are evaluated based on their completion of a real-world project or task that demonstrates their application of knowledge and skills. This form of assessment allows for more authentic evaluation of student abilities and encourages deeper learning.

Educational evaluation is important to assess the effectiveness of educational programs and initiatives. One example of educational evaluation is a pre-post test design to measure the impact of an intervention on student learning outcomes. This approach involves assessing students' knowledge or skills before and after a specific intervention to determine its effectiveness. A strength of this approach is its ability to measure changes in student performance directly related to the intervention. However, a weakness is that it may not account for other factors that could influence student outcomes.

• Hiba Ahmed Mohammed Khamis

A learning and assessment environment that provides learning analytics that can be found in digital learning platforms such as Coursera, Khan Academy, and edX, as well as learning management systems (LMS) like Canvas and Blackboard. These environments use learning analytics to collect, analyze, and use data to improve learning and teaching.
Coursera is a prominent example of a learning environment that offers learning analytics.
How Learning Analytics Works
1. Data Collection:
- Learning Behavior: Data is collected from learners' behaviors as they interact with the learning platform, such as time taken to complete assignments, number of visits to learning materials, and attendance. Participate in discussion activities.
- Assessment Results: Results from tests, assignments, and other forms of assessment are also collected.
- Personal Information: Learners' demographic data and personal information can also be used for analysis.
2. Data Analysis
- Descriptive Analytics: Describe current data to better understand learner behavior and performance.
- Predictive Analytics: Use statistical models and machine learning to predict future outcomes, such as risk of dropping out of school or ability to achieve learning goals.
- Prescriptive Analytics: Provide suggestions and recommendations based on analytical data to improve learning outcomes.
3. Data Visualization:
- Dashboards and Reports: Display data information through dashboards and reports so teachers and students can easily monitor and better understand learning progress and performance.
- Alerts and Notifications: Send alerts and notifications to learners and teachers about issues of concern or learning suggestions.
Effects of Learning Analytics
1. Personalize Learning:
- Customized Learning Content: Based on analytical data, the platform can provide learning content tailored to each student's needs and abilities.
- Personalized Learning Path: Build a learning path based on analysis results to help students achieve their learning goals more effectively.
2. Improve Teaching Effectiveness:
- Instant Feedback: Teachers receive immediate feedback on student performance and the effectiveness of teaching methods, so they can make timely adjustments.
- Early Detection of Problems: Helps teachers detect students' learning problems early and intervene promptly.
3. Enhance Interaction and Engagement:
- Interactive Activities: Suggestions and recommendations for interactive activities based on data analysis help increase student engagement with learning content.
- Learning Motivation: Learning analytics can help motivate learning by providing positive feedback and learning rewards.
4. Management and Decision Making:
Decision-Based Data: Education administrators can use data analytics to make strategic decisions about curriculum development, resource allocation, and student support.

• Phu Cao Tan

Integrating learning analytics into educational environments offers great potential for personalized learning, early prediction and intervention, improved teaching quality, and effective management. However, this also requires facing many challenges, including security and privacy, technology access and use, data quality, feedback and action, and investment and costs. By addressing these challenges, educational institutions can leverage the potential of learning analytics to the greatest benefit for students and teachers.

• Phu Cao Tan

With the implementation of Learning Analytics in the classroom, teachers or educators can detect and track risky students from the perspective of academic failure and then plan, structure and provide actions and initiatives to help and assist the students in practising improvement.
The adoption of smart digital technologies in the education system has grown exponentially over the years, creating new possibilities to improve teaching and enhance learning. Against this backdrop, the ‘brick-and-mortar’ education approach survives on life support, with digital technologies promoting ubiquitous teaching and learning. The advancement of technologies provides a new paradigm of learning, revolutionises knowledge construction, and extends and enriches the ‘brick-and-mortar’ learning environment to enhance the educational experience.

• Ana Babic

Enhancing teaching and learning experiences can be greatly increased by integrating learning analytics into educational settings. But it also poses a number of difficulties:

Prospects:

Personalized Learning: With the help of learning analytics, teachers may efficiently adapt their lessons to each student's unique needs by gaining information into their preferences, learning styles, and progress.

Early Intervention: Learning analytics allows educators to quickly intervene with tailored support and resources by identifying children who may be struggling or at risk of falling behind by evaluating student data in real-time.

Data-Informed Decision Making: By using learning analytics to gather empirical support for their conclusions about student learning patterns and results, educators can use this information to guide curriculum design, instructional planning, and policy decisions.

Continuous Improvement: By facilitating continuous assessment and feedback loops, learning analytics help teachers keep an eye on the success of their interventions and instructional tactics and make gradual, incremental adjustments.

Problems:

Ethical and privacy considerations are brought up by the collection and analysis of sensitive student data, especially when it comes to data security, permission, and possible information misuse. To preserve openness and confidence, learning analytics must be used in an ethical and responsible manner.

Data Quality and Interpretation: Learning analytics's precision and dependability are contingent upon the caliber of the data gathered and the soundness of the algorithms employed in its analysis. The relevance and dependability of analytics insights must be closely assessed by educators in order to prevent erroneous interpretations or biased decision-making.

Infrastructure and Technical Know-How: Learning analytics system implementation calls for a strong technological foundation as well as knowledge of data storage, processing, analysis, and visualization. It's possible that many educational institutions lack the tools or expertise needed to implement and manage these kinds of systems.

User Acceptance and Engagement: Teachers and students' willingness to adopt learning analytics may differ; some may be reluctant to adopt the technology due to concerns about accountability, monitoring, or change. Establishing buy-in, trust, and awareness among stakeholders is crucial to the implementation's success.

Knewton is an illustration of a learning and assessment platform that provides learning analytics: Knewton is an adaptive learning platform that enables students' learning experiences to be personalized through the use of machine learning algorithms and advanced learning analytics. It gathers information about how students engage with digital materials, including exercises, tests, and textbooks, and then utilizes that information to provide tailored suggestions and flexible learning paths.

How to Use It: To determine students' knowledge gaps, preferred methods of learning, and skill levels, Knewton monitors their answers to questions, the amount of time they spend on assignments, and other behavioral data. Knewton uses this data to dynamically modify the level of difficulty and the order of the learning materials, offer focused enrichment or remedial exercises, and give teachers and students real-time feedback.

Impacts: Better Learning Outcomes: By offering individualized help and challenges, Knewton's adaptive learning features have been demonstrated to increase student engagement, retention, and comprehension of course material.

Data-Driven Insights: Teachers can make data-driven decisions and interventions by using dashboards and reports that show student progress, performance patterns, and areas of trouble.

Enhanced Efficiency: Knewton saves teachers time and effort when it comes to grading assignments and customizing lessons by automating some areas of assessment and customisation.

• Bao Thanh Ho

Social Assumptions and Consequences of Different Assessments:

Intelligence Testing:

Assumptions: Intelligence tests often assume a universal definition of intelligence based on cognitive abilities. They may prioritize certain skills (e.g., problem-solving, logical reasoning) over others (e.g., emotional intelligence, creativity).
Consequences for Learners:
Positive: Can identify academic potential and guide educational interventions for those with specific cognitive profiles.
Negative: May reinforce stereotypes or biases if tests are culturally biased or fail to account for diverse forms of intelligence.
Knowledge Testing:

Assumptions: Knowledge tests assume that mastery of specific content or skills reflects competence and readiness for roles or tasks.
Consequences for Learners:
Positive: Encourages mastery of subject matter and can serve as a reliable measure of acquired skills or qualifications.
Negative: Can promote rote memorization and discourage critical thinking or application of knowledge in novel contexts.
Example of Alternative Assessment: Project-Based Learning

Description:
Project-based learning (PBL) is an instructional approach where students actively explore real-world challenges and problems. Instead of traditional tests, students demonstrate knowledge and skills through the completion of projects or tasks.

Analysis:

Strengths:

Authentic Learning: Encourages application of knowledge in real-world scenarios, fostering deeper understanding.
Diverse Skills: Develops collaboration, communication, and problem-solving skills beyond academic content.
Personalization: Allows for individualized projects catering to students' interests and strengths.
Weaknesses:

Time-Intensive: Designing and implementing projects may require substantial time and resources.
Assessment Challenges: Grading can be subjective, requiring clear rubrics and criteria to ensure consistency.
Resource Equity: Access to resources and support outside the classroom can impact project outcomes.
Social Assumptions and Consequences:
Project-based learning challenges traditional assessment assumptions by emphasizing holistic skills and competencies beyond standardized testing. It promotes inclusivity by valuing diverse talents and backgrounds. However, its effectiveness can vary based on resources and support available to students, potentially exacerbating disparities in education.

In conclusion, alternative forms of assessment like project-based learning offer opportunities to address the limitations and biases associated with traditional intelligence and knowledge testing. By prioritizing real-world application and holistic skill development, these approaches can better prepare learners for success in diverse contexts. However, careful consideration of resources, equity, and assessment frameworks is essential to ensure meaningful and equitable learning experiences.

• User User

When we dive into the realm of learning analytics within educational settings, we're looking at a landscape that's as promising as it is complicated. The promise lies in the potential for a truly tailored educational experience. Imagine a classroom where learning is so personalized that each student is met exactly where they stand, intellectually and developmentally. This is what learning analytics can offer – a chance to revolutionize how we teach and learn by using data to sharpen the focus on individual needs and paths to success. The insights gleaned from this data can lead to better outcomes for students, as it empowers educators to refine their teaching to be more effective, and it enables interventions to be precisely timed to support students who might otherwise falter.

But as with any powerful tool, there are risks and challenges. The safeguarding of student data is a serious responsibility; it's not just about following laws, but about earning the trust of those whose information we're handling. Setting up the infrastructure to support learning analytics isn't trivial either – it demands significant investment, both in terms of technology and in the training required to use it effectively. There's a steep learning curve here for everyone involved.

And then there's the matter of interpretation. Data doesn't speak for itself; it needs to be read and understood in context. This means that educators and students alike must become adept at making sense of the information that's being collected. We must also remember that numbers don't capture everything. The qualitative aspects of learning – the discussions, the eureka moments, the personal breakthroughs – are harder to quantify and yet are essential to the full educational picture.

Lastly, we must be vigilant about equity. Data can be biased; it can reflect and amplify existing inequalities if we're not careful. So, as we implement learning analytics, we need to be as committed to fairness and inclusion as we are to innovation and efficiency. After all, the ultimate goal of education is to lift everyone up, not to inadvertently leave some behind.

@Sugam J Shivhare,@William Murphy

• Abdisamad Omar

Accessibility: One of the major advantages of educational technology for learning on the go is its accessibility. With the ubiquity of mobile devices such as smartphones and tablets, learners can access educational content at their convenience. Whether it's watching educational videos, participating in online discussions, or accessing digital textbooks, EdTech ensures that learning resources are readily available, removing constraints of time and location.

For example, platforms like Khan Academy and Coursera offer a wide range of courses that can be accessed on mobile devices. Learners can engage with content whenever they have a few spare minutes, whether it's during their daily commute or while waiting in line.@Rana Masarweh,@Sugam J Shivhare,@William Murphy,@Antonio F Bertachini A Prado,@Kiran Chaudhary,

• Mohammed Mohammed

التقييم والتقويم يندرج كلّ من التقييم والتقويم تحت قائمة العمليات الإدارية الاستراتيجية العصرية التي تلعب دوراً بارزاً في العملية الإدارية الكلية التي تهدف بصورة مباشرة إلى تحقيق غايات وأهداف المؤسسات والمنظمات العاملة في القطاعات المختلفة، حيث يمثلان المراحل الأخيرة في كلّاً من التخطيط الاستراتيجي والإدارة الاستراتيجية، ونجد أنّه قد لبس لدى فئة كبيرة من الأشخاص في التفريق بين هذين المفهومين، مما خلق حالة من الخلط بين المفاهيم، حيث إنّ هناك فرق واضح وشاسع بين كل منهما، ونظراً لذلك اخترنا أن نستعرض بشكل مفصل مفهوم كلاً منهما بشكل منفصل عن الآخر. مفهوم التقييم إنّ عملية التقييم هي عبارة عن نشاط إداري يقيس بدقة مدى تحقيق الأهداف والغايات المطلوبة، ويتمحور حول نشاطين رئيسين يتابعان عملية التنفيذ، ويرصدان الأخطاء فيها، ويقدمان تقريراً بذلك لاتخاذ القرار المناسب بشأنها، وتشكل المرحلة ما قبل الأخيرة من مراحل وضع استراتيجية إدارة الموارد البشرية، حيث نطرح في هذه المرحلة سؤال هل حققنا الهدف، وتتطلب الإجابة على هذا السؤال فحصاً دقيقاً لآلية العمل وخطواته، بصورة تضمن قياس الأداء الذي يتيح فرصة المقارنة الحقيقية بين الأداء المخطط له مسبقاً والأداء الفعلي، وتحديد الانحرافات. إعلان

إقرأ المزيد على موضوع.كوم: https://mawdoo3.com/%D9%85%D9%81%D9%87%D9%88%D9%85_%D8%A7%D9%84%D8%AA%D9%82%D9%8A%D9%8A%D9%85_%D9%88%D8%A7%D9%84%D8%AA%D9%82%D9%88%D9%8A%D9%85

• Mohammed Mohammed

كيف سيستفيد الطلاب من التقييم القائم على المعايير؟
مع التقييم القائم على المعايير، سيتم تصنيف الطلاب وفقا للعوامل الأكاديمية والسلوكية طوال العام الدراسي أو الفصل الدراسي. لا يتعلق مقياس الدرجات الجديد بتسجيل درجات (A إلي F)، ولكنه يهتم ب

التمكن (Mastery) والتقدم نحو الإتقان (progressing toward mastery) والبدأ في التقدم نحو الإتقان (beginning to progress toward mastery) ولم يُظهر التقدم بعد (not yet demonstrating progress)

سيتمكن الطلاب مما يلي:

إظهار موقف أكثر إيجابية وتحفيزا تجاه التعلم
تعلم أهمية التعلم المستقل
لمس قيمة المادة التعليمية
تجربة تحديات جديدة
الانخراط في الصف
التركيز على النجاح بدلا من الابتعاد عن الفشل فقط
ذلك أن العديد من المدارس في مختلف أنحاء العالم تبنت فكرة التقييم القائم على المعايير لعقود من الزمان. فيعد التقييم القائم على المعايير طريقة لعرض تقدم الطلاب بشكل شامل.

ومن المؤكد أنه مفيد للمعلمين حيث سيجدون أن تدريسهم في المكان الصحيح وأنه أكثر صلة بالموضوع. أما بالنسبة إلى الطلاب، فيعد التحفيز النتيجة النهائية العظيمة لهذا النظام والذي بدوره سيؤدي إلى نتيجة مثمرة.

• Mohammed Mohammed