We found 76 results that contain "text"

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).

Primer text from the College of William & Mary.https://education.wm.edu/centers/ttac/documents/packets/adhd.pdfMany students with ADHD have significant difficulties with organization. 
They are more likely to respond positively when teachers establish class routines and set procedures and maintain a well-organized learning environment. Clear rules and advanced planning are keys to success for teachers of students with ADHD.The following organizational supports are particularly useful. Students should be taught to use these tools through teacher modeling and guided practice with feedback before being expected to use them more independently.Assignment Notebook: Provide the student with an assignment notebook to helporganize homework and seatwork.Color-Coded Folders: Provide the student with color-coded folders to helporganize assignments for different academic subjects.Homework Partners: Assign the student a partner who can help record

Key Method
Educator provides evidence of their understanding of communication and outlines and provides evidence of a lesson that uses technology to support students’ use of communication in learning.
Method Components
What are the 4Cs?
The 4Cs for 21st century learning are Creativity, Critical Thinking, Communication, and Collaboration. They are part of the framework for 21st Century Learning and are designed to support student learning in today’s world and are skills they can use in college and career.
What is communication (and what isn’t it)?
The P21 framework emphasizes effective use of oral, written, and nonverbal communication skills for multiple purposes (e.g., to inform, instruct, motivate, persuade, and share ideas). It also focuses on effective listening, using technology to communicate, and being able to evaluate the effectiveness of communication efforts—all within diverse contexts (adapted from P21). Note that working in partners is a great way to collaborate or build shared understanding but a critical part of communication is sharing with an authentic audience.

Educator provides evidence
of their understanding of communication and outlines and provides evidence of a lesson that uses technology to support students’ use of communication in learning.
Method Components
What are the 4Cs?
The 4Cs for 21st century learning are Creativity, Critical Thinking, Communication, and Collaboration. They are part of the framework for 21st Century Learning and are designed to support student learning in today’s world and are skills they can use in college and career.
What is communication (and what isn’t it)?
The P21 framework emphasizes effective use of oral, written, and nonverbal communication skills for multiple purposes (e.g., to inform, instruct, motivate, persuade, and share ideas). It also focuses on effective listening, using technology to communicate, and being able to evaluate the effectiveness of communication efforts—all within diverse contexts (adapted from P21). Note that working in partners is a great way to collaborate or build shared understanding but a critical part of communication is sharing with an authentic audience.
Example strategies that use technology to support communication in the classroom:

Host a TED-style conference or showcases for your students to present original ideas on a topic of interest to them to an authentic, external audience. Record and post the videos to a youtube stream.
Provide opportunities to listen and ask questions through back channel tools like Today’s Meet or even Twitter.
Have your students publish their work through blogs, by creating websites, and by building other online resources that are shared with authentic audiences.
For other ideas see the resources below.

Business Intelligence and Data Science are two of the most recurring terms in the digital era. While both of them involve the use of data, they are totally different from one another. Data Science is the bigger pool containing greater information, BI can be thought of as a part of the bigger picture. 
What is Business Intelligence?
Business Intelligence is a process of collecting, integrating, analyzing, and presenting the data. With Business Intelligence, executives and managers can have a better understanding of decision-making. This process is carried out through software services and tools.
Using Business Intelligence, organizations are able to several strategic and operational business decisions. Furthermore, BI tools are used for the analysis and creation of reports. They are also used for producing graphs, dashboards, summaries, and charts to help the business executives to make better decisions.

Big data:Big data refers to the large, diverse sets of information that grow at ever-increasing rates. It encompasses the volume of information, the velocity or speed at which it is created and collected, and the variety or scope of the data points being covered (known as the "three v's" of big data).

Big data is a great quantity of diverse information that arrives in increasing volumes and with ever-higher velocity.
Big data can be structured (often numeric, easily formatted and stored) or unstructured (more free-form, less quantifiable).
Nearly every department in a company can utilize findings from big data analysis, but handling its clutter and noise can pose problems.
Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins.
Big data is most often stored in computer databases and is analyzed using software specifically designed to handle large, complex data sets.
How Big Data Works
Big data can be categorized as unstructured or structured. Structured data consists of information already managed by the organization in databases and spreadsheets; it is frequently numeric in nature. Unstructured data is information that is unorganized and does not fall into a predetermined model or format. It includes data gathered from social media sources, which help institutions gather information on customer needs.






 






Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins. The presence of sensors and other inputs in smart devices allows for data to be gathered across a broad spectrum of situations and circumstances.

Primer text from The College of William & MaryADHD is one of the most commonly diagnosed conditions of children (Centers for DiseaseControl and Prevention, 2015). 

In a 2016 Centers for Disease Control and Prevention study, scientists found that 6.1 million children aged 2-17 years living in the U.S. had been diagnosed with attention-deficit/hyperactivity disorder (ADHD), which is similar to previous en

Ages 6-11: Approximately 2.4 million children
Ages 12-17: Approximately 3.3 million children


The diagnostic term attention deficit/hyperactivity disorder (ADHD) refers to individuals who display patterns of inattention, impulsivity, and overactive behavior that interfere with daily functioning (American Psychiatric Association [APA], 2013).