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Mobile E-Learning Quiz

Total questions: 35

Worksheet time: 20mins

Name
Class
Date
1.

What are mobile e-learning platforms?

a)

Digital platforms or applications that provide educational content and resources through mobile devices.

b)

Social media platforms that allow users to share educational content.

c)

Websites that offer online courses for mobile users.

d)

Physical classrooms equipped with mobile devices for learning purposes.

2.

Name one popular mobile e-learning platform.

a)

Udemy

b)

Coursera

c)

edX

d)

Khan Academy

3.

What are mobile e-learning apps?

a)

Applications designed for delivering educational content through mobile devices.

b)

Applications designed for delivering entertainment content through mobile devices.

c)

Applications designed for delivering food through mobile devices.

d)

Applications designed for delivering medical content through mobile devices.

4.

Which type of devices are mobile e-learning apps designed for?

a)

Tablets

b)

Desktop computers

c)

Mobile devices

d)

Laptops

5.

What are some common features of mobile e-learning apps?

a)

video tutorials, virtual reality simulations, live streaming classes, offline access

b)

gamification elements, discussion forums, language translation, offline access

c)

flashcards, virtual reality simulations, progress tracking and reporting, personalized learning paths

d)

interactive quizzes and assessments, multimedia content, progress tracking and reporting, personalized learning paths, social learning features

6.

What are mobile e-learning strategies?

a)

Methods and approaches used to deliver educational content through mobile devices.

b)

Techniques for securing mobile devices.

c)

Strategies for marketing mobile apps.

d)

Ways to improve mobile phone battery life.

7.

Name one effective mobile e-learning strategy.

a)

Gamification

b)

Long-form video lectures

c)

Microlearning

d)

Traditional classroom learning

8.

What factors contribute to the effectiveness of mobile e-learning?

a)

Factors that contribute to the effectiveness of mobile e-learning include slow internet connection, outdated technology, and limited storage capacity.

b)

Factors that contribute to the effectiveness of mobile e-learning include accessibility, convenience, personalization, interactivity, and multimedia capabilities.

c)

Factors that contribute to the effectiveness of mobile e-learning include lack of user engagement, poor user interface, and limited device compatibility.

d)

Factors that contribute to the effectiveness of mobile e-learning include high cost, limited content, and lack of technical support.

9.

What are the advantages of mobile e-learning over traditional e-learning?

a)

Higher cost, limited access to resources, lack of personalization, lack of interactivity

b)

Less flexibility, limited availability, lack of customization, lack of engagement

c)

Inconvenience, restricted learning opportunities, lack of individualization, lack of collaboration

d)

Accessibility, convenience, personalized learning experience, interactivity

10.

What are some potential challenges of implementing mobile e-learning?

a)

Limited screen size, compatibility issues, connectivity issues, and mobile device management.

b)

High cost of implementation, Lack of technical support, Limited storage capacity

11.

MALL stands for …

a)

Mobile-assisted language learning

b)

Mobile-assurance language learning

c)

Mobility and advancement in language learning

d)

Mobile-enhanced language learning

12.

Mobile technologies offer benefits as follows, except …

a)

Flexibility

b)

User-friendliness

c)

Quantity

d)

Small size

13.

MALL is defined as …

a)

a way to enable people to learn through handheld devices due to its versatility, flexibility and interactivity

b)

The average rating of the learners using mobile flashcards is

bigger than those using traditional flashcards

c)

a method to enable people to learn through automobile due to its flexibility

d)

any learning activity that is happening by taking the advantage of computer technology

14.

How can teachers utilize social networking tools for their teaching activity?

a)

By monitoring students’ life from their feeds

b)

By asking students interacting with each other in a myriad of ways

c)

By randomly follow native speakers and chat with them

d)

By interacting asynchronously with anyone in the social media

15.

The following are some benefits found in the use of video recording for students, EXCEPT…

a)

integrating digital video recording into speaking course improves their oral communication

b)

learners can do some meaningful repetitions to produce the best oral performance

c)

video recording enables the learners to take risks in the target language

d)

video recording increases students anxiety of speaking in front of the camera

16.

This application is used as a micro-blogging app

a)

Notes

b)

Voice memory

c)

Text message

d)

Twitter

17.

Vlogging activity can help students improve their … skill in English

a)

Speaking

b)

Writing

c)

Listening

d)

Reading

18.

Mobile phone feature that help students record interviews or conversations outside the classroom is …

a)

Notes

b)

Voice memory

c)

Text message

d)

Twitter

19.

The application used to do surveys is …

a)

Notes

b)

Twitter

c)

Skype

d)

Polleverywhere

20.

The application that allows the students to exchange native language verbally is …

a)

Notes

b)

Twitter

c)

Skype

d)

Polleverywhere

21.

What is Machine Learning? (Choose 3 Answers)

a)

Artificial Intelligence

b)

Machine Learning

c)

Data Statistics

d)

Deep Learning

22.

Which one in the following is not Machine Learning disciplines?

a)

Information Theory

b)

Neurostatistics

c)

Optimization + Control

d)

Physics

23.

from the picture, what kind of programming is it?

a)

Traditional Programming

b)

Modern Programming

c)

Machine Learning

d)

Traditional Learning

24.

from the picture, what kind of programming is it?

a)

Traditional Programming

b)

Machine Learning

c)

Modern Programming

d)

Traditional Learning

25.

What kind of learning algorithm for "Future stock prices or currency exchange rates"?

a)

Recognizing Anomalies

b)

Prediction

c)

Generating Patterns

d)

Recognition Patterns

26.

What kind of learning algorithm for "Facial identities or facial expressions"?

a)

Recognizing Anomalies

b)

Prediction

c)

Generating Patterns

d)

Recognition Patterns

27.

Which of the following is not type of learning?

a)

Semi-unsupervised Learning

b)

Unsupervised Learning

c)

Supervised Learning

d)

Reinforcement Learning

28.

Real-Time decisions, Game AI, Learning Tasks, Skill Aquisition, and Robot Navigation are applications in ...

a)

Unsupervised Learning: Clustering

b)

Supervised Learning: Classification

c)

Reinforcement Learning

d)

Unsupervised Learning: Regression

29.

Targetted marketing, Recommended Systems, and Customer Segmentation are applications in ...

a)

Unsupervised Learning: Clustering

b)

Supervised Learning: Classification

c)

Reinforcement Learning

d)

Unsupervised Learning: Regression

30.

Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...

a)

Unsupervised Learning: Clustering

b)

Supervised Learning: Classification

c)

Reinforcement Learning

d)

Unsupervised Learning: Regression

31.

This picture shows a result of ...

a)

Supervised Learning: Classification

b)

Unsupervised Learning: Regression

c)

Unsupervised Learning: Prediction

d)

Supervised Learning: Regression

32.

This picture shows an application of ...

a)

Supervised Learning: Classification

b)

Unsupervised Learning: Clustering

c)

Unsupervised Learning: Prediction

d)

Supervised Learning: Regression

33.

Machine Learning has various function representation, which of the following is not function of symbolic?

a)

Decision Trees

b)

Rules in propotional Logic

c)

Hidden-Markov Models (HMM)

d)

Rules in first-order predicate logic

34.

Machine Learning has various function representation, which of the following is not numerical functions?

a)

Linear Regression

b)

Support Vector Machines

c)

Neural Network

d)

Case-based

35.

Machine Learning has various search/ optimization algorithms, which of the following is not evolutionary computation?

a)

Perceptron

b)

Genetic Algorithm (GA)

c)

Neuro Evolution

d)

Genetic Programming (GP)