6. From an ethical perspective, what is necessary to promote Inclusivity and Accessibility in AI Education?”

B) Address AI biases, ensure equal access to educational resources for all.

4. What is a significant obstacle when incorporating Learning Analytics in AIEd, from a Determinist perspective?”

C) Ethical issues concerning the data protection and biases in algorithms.

1. How does AI in Education (AIEd) lead to change in teaching methods, as explained by Determinist Theory?

C) Promoting tailored learning experiences and adapting to individual need.

2. In what way does Automation in AI Education support the views of Instrumentalist Theory ?

B) It simplifies administrative duties to focus on tailored teaching.

5. Concerns regarding Bias and Fairness in AI in Education often stem from:

A) The data-driven nature of AI systems may reflect existing prejudices.

3. What is a likely benefit of Personalised Learning through AI in Education (AIEd), as per Instrumentalist Theory?

D) Better support for various educational needs and learning preferences.

studbud

AI in Education Quiz

6 termsStudBud Administration13 plays

Artificial Intelligence in Education (AIEd) research suggests theories about the interactions between humans and technology. This Quiz uses questions about the perspectives from Instrumentalist and Determinist theories on AI in Education to give examples of potential pro's and con's of AIEd. Have Fun!

Flashcards6 cardsFPractice quizPHost liveL

Questions 6

Answers

1
6. From an ethical perspective, what is necessary to promote Inclusivity and Accessibility in AI Education?”
B) Address AI biases, ensure equal access to educational resources for all.
A) Concentrate only on the most advanced educational technologies.
D) Prioritise development of AI systems over educator training development.
C) Limit AI in Education usage to progressive educational institutions.
2
4. What is a significant obstacle when incorporating Learning Analytics in AIEd, from a Determinist perspective?”
C) Ethical issues concerning the data protection and biases in algorithms.
A) The challenge of providing immediate data analysis and feedback.
B) The tendency to prioritise numerical data over observational insights.
D) Resistance from educational institutions to adopt new technologies.
3
1. How does AI in Education (AIEd) lead to change in teaching methods, as explained by Determinist Theory?
B) Advocating for traditional practices without technological intervention.
A) Emphasising teacher-centred approaches and reducing student autonomy.
C) Promoting tailored learning experiences and adapting to individual need.
D) Encouraging rote memorization and standardised testing.
4
2. In what way does Automation in AI Education support the views of Instrumentalist Theory ?
C) It imposes a one-size-fits-all educational method for students.
B) It simplifies administrative duties to focus on tailored teaching.
A) It eliminates the necessity for educators and personal interaction.
D) It lessens the value of student input in customising learning.
5
5. Concerns regarding Bias and Fairness in AI in Education often stem from:
C) The complexity of algorithms and their lack of transparency.
B) The digital-divide and unequal access to technology.
A) The data-driven nature of AI systems may reflect existing prejudices.
D) Over-reliance on AIEd systems to make critical educational decisions.
6
3. What is a likely benefit of Personalised Learning through AI in Education (AIEd), as per Instrumentalist Theory?
D) Better support for various educational needs and learning preferences.
B) Increased focus on academic competition.
C) Decreased necessity for face-to-face teaching.
A) Improved delivery efficiency of standardised educational material.

AI in Education Quiz Flashcards | StudBud

AI in Education Quiz

6 termsStudBud Administration13 plays

Flashcards6 cardsFPractice quizPHost liveL

Questions 6

Answers

1
6. From an ethical perspective, what is necessary to promote Inclusivity and Accessibility in AI Education?”
B) Address AI biases, ensure equal access to educational resources for all.
A) Concentrate only on the most advanced educational technologies.
D) Prioritise development of AI systems over educator training development.
C) Limit AI in Education usage to progressive educational institutions.
2
4. What is a significant obstacle when incorporating Learning Analytics in AIEd, from a Determinist perspective?”
C) Ethical issues concerning the data protection and biases in algorithms.
A) The challenge of providing immediate data analysis and feedback.
B) The tendency to prioritise numerical data over observational insights.
D) Resistance from educational institutions to adopt new technologies.
3
1. How does AI in Education (AIEd) lead to change in teaching methods, as explained by Determinist Theory?
B) Advocating for traditional practices without technological intervention.
A) Emphasising teacher-centred approaches and reducing student autonomy.
C) Promoting tailored learning experiences and adapting to individual need.
D) Encouraging rote memorization and standardised testing.
4
2. In what way does Automation in AI Education support the views of Instrumentalist Theory ?
C) It imposes a one-size-fits-all educational method for students.
B) It simplifies administrative duties to focus on tailored teaching.
A) It eliminates the necessity for educators and personal interaction.
D) It lessens the value of student input in customising learning.
5
5. Concerns regarding Bias and Fairness in AI in Education often stem from:
C) The complexity of algorithms and their lack of transparency.
B) The digital-divide and unequal access to technology.
A) The data-driven nature of AI systems may reflect existing prejudices.
D) Over-reliance on AIEd systems to make critical educational decisions.
6
3. What is a likely benefit of Personalised Learning through AI in Education (AIEd), as per Instrumentalist Theory?
D) Better support for various educational needs and learning preferences.
B) Increased focus on academic competition.
C) Decreased necessity for face-to-face teaching.
A) Improved delivery efficiency of standardised educational material.