We found 68 results that contain "education system"

 Teaching Commons: “an emergent conceptual space for exchange and community among faculty, students, and all others committed to learning as an essential activity of life in contemporary democratic society” (Huber and Hutchings, 2005, p.1) What Is the #iteachmsu Commons?    You teach MSU. We, the Academic Advancement Network, The Graduate School, and The Hub for Innovation in Learning and Technology, believe that a wide educator community (faculty, TAs, ULAs, instructional designers, academic advisors, et al.) makes learning happen across MSU. But, on such a large campus, it can be difficult to fully recognize and leverage this community’s teaching and learning innovations. To address this challenge, the #iteachmsu Commons provides an educator-driven space for sharing teaching resources, connecting across educator networks, and growing teaching practice. #iteachmsu Commons content may be discipline-specific or transdisciplinary, but will always be anchored in teaching competency areas. You will find blog posts, curated playlists, educator learning module pathways, and a campus-wide teaching and learning events calendar. We cultivate this commons across spaces. And through your engagement, we will continue to nurture a culture of teaching and learning across MSU and beyond. How Do I Contribute to the #iteachmsu Commons? Content is organized by posts, playlists and pathways.

Posts: Posts are shorter or longer-form blog postings about teaching practice(s), questions for the educator community, and/or upcoming teaching and learning events. With an MSU email address and free account signup, educators can immediately contribute blog posts and connected media (e.g. handouts, slide decks, class activity prompts, promotional materials). All educators at MSU are welcome to use and contribute to #iteachmsu. And there are no traditional editorial calendars. Suggested models of posts can be found here.
Playlists: Playlists are groupings of posts curated by individual educators and the #iteachmsu community. Playlists allow individual educators to tailor their development and community experiences based on teaching competency area, interest, and/or discipline.
Pathways: Pathways are groupings of educator learning modules curated by academic and support units for badges and other credentialing.

There are two ways to add your contribution to the space:

Contribute existing local resources for posts and pathways: Your unit, college, and/or department might already have educator development resources that could be of use to the wider MSU teaching and learning community. These could be existing blog posts on teaching practice, teaching webinars, and/or open educational resources (e.g classroom assessments, activities). This content will make up part of the posts, playlists, and pathways on this site. Educators can then curate these posts into playlists based on their individual interests. Please make sure to have permission to share this content on a central MSU web space.
Contribute new content for posts: A strength of the #iteachmsu Commons is that it immediately allows educators to share teaching resources, questions and events through posts to the entire community. Posts can take a variety of forms and are organized by teaching competency area categories, content tags, date, and popularity. Posts can be submitted by both individual educators and central units for immediate posting but must adhere to #iteachmsu Commons community guidelines. Posts could be:




About your teaching practice(s): You discuss and/or reflect on the practices you’re using in your teaching. In addition to talking about your ideas, successes, and challenges, we hope you also provide the teaching materials you used (sharing the assignment, slidedeck, rubric, etc.)
Responses to teaching ideas across the web or social media: You share your thoughts about teaching ideas they engage with from other media across the web (e.g. blog posts, social media posts, etc.).
Cross-posts from other teaching-related blogs that might be useful for the #iteachmsu community: You cross-post content from other teaching-related blogs they feel might be useful to the #iteachmsu community.
About teaching-related events: You share upcoming teaching related events as well as their thoughts about ideas they engage with events at MSU and beyond (e.g. workshops, conferences, etc.). If these events help you think in new ways about your practice, share them with the #iteachmsu community.
Questions for our community: You pose questions via posts to the larger community to get ideas for their practice and connect with others considering similar questions.



What Are the #iteachmsu Commons Policies?Part of the mission of the #iteachmsu Commons is to provide space for sharing, reflecting, and learning for all educators on our campus wherever they are in their teaching development. The commons is designed to encourage these types of interactions and reflect policies outlined by the MSU Faculty Senate.  We maintain the right to remove any post that violates guidelines as outlined here and by MSU. To maintain a useful and safer commons, we ask that you:

Follow the MSU Guidelines for Social Media.
Engage across the #iteachmsu commons in a civil and respectful manner. Content may be moderated in accordance with the MSU Guidelines for Social Media.
Do not share private or confidential information via shared content on the #iteachmsu Commons.

Content posted on the #iteachmsu Commons is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license. Learn more about this licensing here. Posted comments, images, etc. on the #iteachmsu Commons do not necessarily represent the views of Michigan State University or the #iteachmsu Commons Team. Links to external, non-#iteachmsu Commons content do not constitute official endorsement by, or necessarily represent the views of, the #iteachmsu Commons or Michigan State University. What if I Have #iteachmsu Commons Questions and/or Feedback?If you have any concerns about #iteachmsu Commons content, please email us at iteach@msu.edu. We welcome all feedback and thank you for your help in promoting a safer, vibrant and respectful community.  

Technology acceptance model

 
 


Based on the theory of reasoned Action, Davis ( 1986 ) developed the Technology Acceptance Model which deals more specifically with the prediction of the acceptability of an information system. The purpose of this model is to predict the acceptability of a tool and to identify the modifications which must be brought to the system in order to make it acceptable to users. This model suggests that the acceptability of an information system is determined by two main factors: perceived usefulness and perceived ease of use.
Perceived usefulness is defined as being the degree to which a person believes that the use of a system will improve his performance. Perceived ease of use refers to the degree to which a person believes that the use of a system will be effortless. Several factorial analyses demonstrated that perceived usefulness and perceived ease of use can be considered as two different dimensions (Hauser et Shugan, 1980 ; Larcker et Lessig, 1980 ; Swanson, 1987).
As demonstrated in the theory of reasoned Action, the Technology Acceptance Model postulates that the use of an information system is determined by the behavioral intention, but on the other hand, that the behavioral intention is determined by the person’s attitude towards the use of the system and also by his perception of its utility. According to Davis, the attitude of an individual is not the only factor that determines his use of a system, but is also based on the impact which it may have on his performance. Therefore, even if an employee does not welcome an information system, the probability that he will use it is high if he perceives that the system will improve his performance at work. Besides, the Technology Acceptance Model hypothesizes a direct link between perceived usefulness and perceived ease of use. With two systems offering the same features, a user will find more useful the one that he finds easier to use (Dillon and Morris, on 1996).

Technology acceptance model

 
 


Based on the theory of reasoned Action, Davis ( 1986 ) developed the Technology Acceptance Model which deals more specifically with the prediction of the acceptability of an information system. The purpose of this model is to predict the acceptability of a tool and to identify the modifications which must be brought to the system in order to make it acceptable to users. This model suggests that the acceptability of an information system is determined by two main factors: perceived usefulness and perceived ease of use.
Perceived usefulness is defined as being the degree to which a person believes that the use of a system will improve his performance. Perceived ease of use refers to the degree to which a person believes that the use of a system will be effortless. Several factorial analyses demonstrated that perceived usefulness and perceived ease of use can be considered as two different dimensions (Hauser et Shugan, 1980 ; Larcker et Lessig, 1980 ; Swanson, 1987).
As demonstrated in the theory of reasoned Action, the Technology Acceptance Model postulates that the use of an information system is determined by the behavioral intention, but on the other hand, that the behavioral intention is determined by the person’s attitude towards the use of the system and also by his perception of its utility. According to Davis, the attitude of an individual is not the only factor that determines his use of a system, but is also based on the impact which it may have on his performance. Therefore, even if an employee does not welcome an information system, the probability that he will use it is high if he perceives that the system will improve his performance at work. Besides, the Technology Acceptance Model hypothesizes a direct link between perceived usefulness and perceived ease of use. With two systems offering the same features, a user will find more useful the one that he finds easier to use (Dillon and Morris, on 1996).

The classic egg drop experiment gets reinvented as a driving question for physics students to explore a real-world problem.

By Suzie Boss
July 26, 2018
When a teenager climbs atop his desk and drops an object to the floor, teacher Johnny Devine doesn’t object. Far from it—he’s as eager as the rest of the class to see what happens next.

In a split second, the student and his teammates get positive feedback for the object they have cobbled together by hand. A small parachute made of plastic and held in place with duct tape opens as planned, slowing the descent and easing the cargo to a safe landing. Students exchange quick smiles of satisfaction as they record data. Their mission isn’t accomplished yet, but today’s test run brings them one step closer to success as aspiring aerospace engineers.



To boost engagement in challenging science content, Devine has his students tackle the same problems that professional scientists and engineers wrestle with. “Right away, they know that what they are learning can be applied to an actual career,” Devine says. “Students are motivated because it’s a real task.”

From the start of Mission to Mars, students know that expert engineers from local aerospace companies will evaluate their final working models of Mars landing devices. Their models will have to reflect the students’ best thinking about how to get a payload from orbit onto the surface of the Red Planet without damaging the goods inside. While real Mars landings involve multimillion-dollar equipment, students’ launchers will carry four fragile eggs.

THE ROAD MAP

Although the project gives students considerable freedom, it unfolds through a series of carefully designed stages, each focused on specific learning goals. Having a detailed project plan “creates a roadmap,” Devine explains, “for the students to really track their progress and see how what they’re learning connects back to the guiding question: How can we successfully land a rover on Mars?”

©George Lucas Educational Foundation

Before introducing technical content, Devine wants students to visualize what space scientists actually do. By watching videos of engineers who design entry, descent, and landing systems for spacecraft, students start getting into character for the work ahead.

Devine introduces a series of hands-on activities as the project unfolds to help students put physics concepts into action. They learn about air resistance, for instance, by experimenting with parachute designs and wrestling with a real challenge: How will they slow their landers to a reasonable speed for entry into the thin Martian atmosphere?

To apply the concept of change in momentum, students design airbag systems to go on the bottom of their landers—a location aptly called the crumple zone. They experiment with bubble wrap and other materials as potential cushioners for their cargo.

As the grand finale approaches, students keep using what they learn to test, analyze, and modify their designs. “You have to repeat the equations with different trials,” one student explains. “Being able to use that math over and over again helps it stick.”

Much of the hands-on learning in this PBL classroom “might look like a traditional physics lab,” Devine acknowledges, with students learning concepts through inquiry investigations. What’s different is the teacher’s ongoing reminder “to make sure students stay in character” as systems engineers. Each lab investigation relates back to their driving question and creates more opportunities for Devine to ask probing questions and formatively assess his students’ understanding. “We do a lot of framing in and framing out after each of those lessons so students have the chance to reflect and connect it back,” the teacher explains.

EXPERT CONVERSATIONS

When it is finally time for students to launch their precious cargo off a second-story landing, engineers from local aerospace companies are standing by to assess results. How many eggs in each lander will survive the fall?

Even more important than the test data are the discussions between experts and students. One engineer, for instance, asks to see earlier versions of a team’s design and hear about the tests that led to modifications. A student named Elizabeth perks up when she hears engineers using the same technical vocabulary that she and her classmates have learned. “It was kind of a connection—this is actually a thing that goes on,” she says.

“They had really deep, meaningful conversations so that students could practice communicating their justification for their designs,” Devine says. Hearing them use academic language and apply physics concepts tells the teacher that students deeply understand the science behind their designs. “At the end of the day, that’s what I’m most concerned about,” he says.

https://youtu.be/bKc2shFqLao


 

Categories of AI
Artificial intelligence:
can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon's Alexa and Apple's Siri. You ask the assistant a question, it answers it for you.
 
Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.
 
 

Block chain technology allows duplication of data. Thus it can help to store digital copies of the student certificates in the distributed and collaborated environment. Each university can act as node or Validator where any person in authority can validate student documents by requesting for verified information from the students.
 
Such collaborative approach can help solve many issues like loss of original degree certificates or mark sheets, illegal duplication or modification of documents, authentication of student education records etc. This will also help universities to cut down the costs involved in making infrastructure available for storage of students’ important educational documents.

Estimating and analyzing the Earth Energy Imbalance (EEI) is essential for understanding the evolution of the Earth’s climate. This is possible only through a careful computation and monitoring of the climate-energy budget. The climate system exchanges energy with outer space at the top of the atmosphere (TOA) (through radiation) and with solid Earth at the Earth’s crust surface (essentially through geothermal flux). If the climate system were free from external perturbations and internal variability during millennia, then the climate-energy budget would be in a steady state in which the net TOA radiation budget compensates the geothermal flux of +0.08 Wm–2 (Davies and Davies, 2010).
But the climate system is not free from external perturbations and from internal variability. Although the geothermal flux does not generate any perturbations at interannual to millennial time scales (because it varies only at geological time scales), other external forcings from natural origin (such as the solar radiation, the volcanic activity) or anthropogenic origin (such as Greenhouse Gas emissions –GHG-) perturb the system.
 
REf:https://www.frontiersin.org/articles/10.3389/fmars.2019.00432/full

https://www.youtube.com/watch?v=xHBhFKBLhWshttps://mays.tamu.edu/department-of-information-and-operations-management/management-information-systems/#:~:text=Management%20Information%20Systems%20(MIS)%20is,emphasis%20on%20service%20through%20technology.