Technology has become a key aspect of our lives and a useful learning tool. This is the focus of this month’s activities, which help our students to reflect on the role technology plays in our lives and how it can help them improve their English. Our B2 First and C1 Advanced students consider the positive and negative sides of technology while they practise their listening, reading and speaking. B1 Preliminary and B2 First students will learn technology vocabulary and write a horror story. Our younger learners can have fun while they learn technology vocabulary and practise their speaking, reading and writing. Happy teaching!

1. 1
October
Technology has become a key aspect of our lives and a useful learning tool. This is the focus
of this month’s activities, which help our students to reflect on the role technology plays in our
lives and how it can help them improve their English. Our B2 First and C1 Advanced students
consider the positive and negative sides of technology while they practise their listening,
reading and speaking. B1 Preliminary and B2 First students will learn technology vocabulary
and write a horror story. Our younger learners can have fun while they learn technology
vocabulary and practise their speaking, reading and writing. Happy teaching!
1. Reading emotions............................................................................................................................2
2. Technology .......................................................................................................................................7
3. Learning tools.................................................................................................................................11
4. References......................................................................................................................................15

2. 2
1. Reading emotions
Level: B2 First / C1 Advanced
Skills: speaking, listening and reading
Interaction: whole class, in pairs and individual activity
Equipment and materials: computer, speakers
Time: 45 minutes
Warm up! (15’) – whole class activity
• How long do you spend on your mobile phone and your computer / laptop?
• Has the amount of time you spend on the Internet increased since last March? Why
(not)?
• What tasks or activities do you usually do using an electronic device or a domestic
appliance? Could you still do these tasks or activities without one?
• Do you feel comfortable sharing personal information online? Why (not)?
• Do you think technology has altered the way you interact with people? Why (not)?
• What are the main advantages of using technology in your daily life?
• What are the main disadvantages of using technology in your daily life?
• Look at the photographs below and explain how they relate to the topic we are
discussing.

3. 3
Listening (20’) – in pairs and individual activity
You are going to watch a short video about machines and emotions. Look at the picture below
and the title and try to predict what the video is about.
You are going to watch the video twice.
Answer the following questions:
1. Why is it dangerous that machines can identify how we feel?
a. Because machines may be able to alter our emotions.
b. Because machines can use this ability to influence or control us.
c. Because machines can imitate our emotions and replace us.
2. How can machines identify our emotions?
a. by changing the way they process data
b. by learning how to spot cultural cues
c. by obtaining visual information and categorising it
3. Which of these is not used to identify emotions according to the video?
a. changes in body temperature
b. writing style
c. eating habits
4. The potential benefits of emotion recognition by machines include:
a. baby-sitting young children.
b. identifying health problems in the elderly.
c. reducing the cost of psychological treatment.

4. 4
Now, in pairs, read the script below and correct your answers. Identify why the incorrect options
are wrong.
With every year, machines surpass humans in more and more activities we once thought only we
were capable of. Today's computers can beat us in complex board games, transcribe speech in
dozens of languages, and instantly identify almost any object. But the robots of tomorrow may go
further by learning to figure out what we're feeling. And why does that matter? Because if machines
and the people who run them can accurately read our emotional states, they may be able to assist
us or manipulate us at unprecedented scales. But before we get there, how can something so
complex as emotion be converted into mere numbers, the only language machines
understand? Essentially the same way our own brains interpret emotions, by learning how to spot
them. American psychologist Paul Ekman identified certain universal emotions whose visual cues
are understood the same way across cultures. For example, an image of a smile signals joy to
modern urban dwellers and aboriginal tribesmen alike. And according to
Ekman, anger, disgust, fear, joy, sadness, and surprise are equally recognizable. As it turns out,
computers are rapidly getting better at image recognition thanks to machine learning algorithms,
such as neural networks. These consist of artificial nodes that mimic our biological neurons by
forming connections and exchanging information. To train the network, sample inputs pre-classified
into different categories, such as photos marked happy or sad, are fed into the system. The network
then learns to classify those samples by adjusting the relative weights assigned to particular
features. The more training data it's given, the better the algorithm becomes at correctly identifying
new images. This is similar to our own brains, which learn from previous experiences to shape how
new stimuli are processed. Recognition algorithms aren't just limited to facial expressions. Our
emotions manifest in many ways. There's body language and vocal tone, changes in heart rate,
complexion, and skin temperature, or even word frequency and sentence structure in our
writing. You might think that training neural networks to recognize these would be a long and
complicated task until you realize just how much data is out there, and how quickly modern
computers can process it. From social media posts, uploaded photos and videos, and phone
recordings, to heat-sensitive security cameras and wearables that monitor physiological signs, the
big question is not how to collect enough data, but what we're going to do with it. There are plenty
of beneficial uses for computerized emotion recognition. Robots using algorithms to identify facial
expressions can help children learn or provide lonely people with a sense of companionship. Social
media companies are considering using algorithms to help prevent suicides by flagging posts that
contain specific words or phrases. And emotion recognition software can help treat mental
disorders or even provide people with low-cost automated psychotherapy. Despite the potential
benefits, the prospect of a massive network automatically scanning our
photos, communications, and physiological signs is also quite disturbing. What are the implications
for our privacy when such impersonal systems are used by corporations to exploit our emotions
through advertising? And what becomes of our rights if authorities think they can identify the people
likely to commit crimes before they even make a conscious decision to act? Robots currently have
a long way to go in distinguishing emotional nuances, like irony, and scales of emotions, just how
happy or sad someone is. Nonetheless, they may eventually be able to accurately read our
emotions and respond to them. Whether they can empathize with our fear of unwanted intrusion,
however, that's another story.

5. 5
Follow up (10’) – whole class activity
• Are you surprised by the information included in this video? Why (not)?
• Imagine that your younger brother or sister has just been given their first smartphone.
What recommendations would you give them?
KEY
With every year, machines surpass humans in more and more activities we once thought only we
were capable of. Today's computers can beat us in complex board games, transcribe speech in
dozens of languages, and instantly identify almost any object. But the robots of tomorrow may go
further by learning to figure out what we're feeling. And why does that matter? Because if machines
and the people who run them can accurately read our emotional states, they may be able to assist
us or manipulate us at unprecedented scales. But before we get there, how can something so
complex as emotion be converted into mere numbers, the only language machines
understand? Essentially the same way our own brains interpret emotions, by learning how to spot
them. American psychologist Paul Ekman identified certain universal emotions whose visual cues
are understood the same way across cultures. For example, an image of a smile signals joy to
modern urban dwellers and aboriginal tribesmen alike. And according to
Ekman, anger, disgust, fear, joy, sadness, and surprise are equally recognizable. As it turns out,
computers are rapidly getting better at image recognition thanks to machine learning algorithms,
such as neural networks. These consist of artificial nodes that mimic our biological neurons by
forming connections and exchanging information. To train the network, sample inputs pre-classified
into different categories, such as photos marked happy or sad, are fed into the system. The network
then learns to classify those samples by adjusting the relative weights assigned to particular
features. The more training data it's given, the better the algorithm becomes at correctly identifying
new images. This is similar to our own brains, which learn from previous experiences to shape how
new stimuli are processed. Recognition algorithms aren't just limited to facial expressions. Our
emotions manifest in many ways. There's body language and vocal tone, changes in heart rate,
complexion, and skin temperature, or even word frequency and sentence structure in our
writing. You might think that training neural networks to recognize these would be a long and
complicated task until you realize just how much data is out there, and how quickly modern
computers can process it. From social media posts, uploaded photos and videos, and phone
recordings, to heat-sensitive security cameras and wearables that monitor physiological signs, the
big question is not how to collect enough data, but what we're going to do with it. There are plenty
of beneficial uses for computerized emotion recognition. Robots using algorithms to identify facial
expressions can help children learn or provide lonely people with a sense of companionship. Social
media companies are considering using algorithms to help prevent suicides by flagging posts that
contain specific words or phrases. And emotion recognition software can help treat mental
disorders or even provide people with low-cost automated psychotherapy. Despite the potential
benefits, the prospect of a massive network automatically scanning our
photos, communications, and physiological signs is also quite disturbing. What are the implications
for our privacy when such impersonal systems are used by corporations to exploit our emotions
through advertising? And what becomes of our rights if authorities think they can identify the people
likely to commit crimes before they even make a conscious decision to act? Robots currently have
a long way to go in distinguishing emotional nuances, like irony, and scales of emotions, just how
happy or sad someone is. Nonetheless, they may eventually be able to accurately read our

6. 6
emotions and respond to them. Whether they can empathize with our fear of unwanted intrusion,
however, that's another story.

7. 7
2. Technology
Level: B1 Preliminary / B2 First
Skills: speaking and writing
Interaction: whole class, group and individual activity
Content: vocabulary related to technology
Time: 50 minutes
Warm up! (10’) – whole class activity
 Look at the pictures below, what topic are we going to work on today?
 How do you feel about technology? Why?
 What are the main advantages of technology?
 What are the main disadvantages of technology?

8. 8
Vocabulary, Speaking and Writing (15’) – group activity
Without moving students, assign students to teams in the same area of the classroom. Choose
one student from each group to note down all their team’s ideas on a large sheet of paper.
Explain that the other side of the poster features 30 topic-related words and phrases. Teams
can earn points by guessing them.
Groups take turns to guess a word or phrase that is on the poster (referring to the lists created
in the previous stage). When they do so, the teacher shouts ‘Snap!’.
Award a point for each word that is correctly guessed, and a bonus point if they can use the
word in a sentence. The group with the most points at the end is the winner.

9. 9
KEY
Writing (25’) – individual activity
Your school has organised a writing competition to celebrate Halloween.
Stories wanted
We are looking for the best horror story featuring technology.
Stories should be written in about 100 words and must begin with…
And then the screen went black.
The best story will be published on the school blog and the writer will be
awarded a new tablet!

10. 10
* Before submitting your story, review it with the Success Criteria.
B1 Preliminary Writing Success Criteria Yes No Comments
Content Yes No Comments
Have you written about all the content points?
Have you added some information about each of them?
Communicative Achievement Yes No Comments
Story
Read your story again, is it clear? Do you need to read
some parts again because you don’t understand them?
Organisation Yes No Comments
Have you used paragraphs for the different ideas?
Have you used connectors such as and, but, so,
because?
Language Yes No Comments
Have you used synonyms?
Have you used a few different grammatical structures?

11. 11
3. Learning tools
Level: A1 Movers, A2 Flyers and A2 Key
Skills: writing, speaking and listening
Interaction: individual, whole class and in pairs
Content: technology vocabulary, prepositions, school
vocabulary
Time: 45 minutes
Warm up! (10’) – individual activity
Look around you. How many objects in the classroom can you name?
Students are given one minute to write down as many classroom words as they know.
Vocabulary (10’) – individual activity / in pairs* (*A1 Movers)
Students read the definitions and do the crossword.

12. 12
Speaking and writing (10’) – whole class activity
How many of the objects for the words in the crossword can you see on this poster?

13. 13
Which of the objects that you can see on this poster did you use when you were learning
from home? Which ones do you use when you are learning face-to-face? Which ones can be
used in both situations?
Writing and reading (15’) – in pairs activity
Write 5 sentences about the poster. Some of them should be true and others should be
false.
Learning face-to-face
whiteboard / blackboard
Learning online
computer
Learning face-to-face
and online
books

14. 14
Sentences
Example: There is a cat outside. T
1.
2.
3.
4.
5.
Swap your sentences with another pair of classmates. Decide if your classmates’ sentences
are true or false.

15. 15
4. References
Cameron, J. M. (2020). Photo of Child Smiling While Using Tablet Computer [image/jpeg].
Available at: https://www.pexels.com/photo/photo-of-child-smiling-while-using-tablet-
computer-4145032/ [Accessed 21st
September 2010].
Cameron, J.M. (2020). Photo of Boy Using Vr Headset. [image/jpeg]. Available at:
https://www.pexels.com/photo/photo-of-boy-using-vr-headset-4145356/ [Accessed
21st
September 2010].
Cottonbro (2020). Person in Gray Button Up Shirt Sitting on Brown Wooden Chair
[image/jpeg]. Available at: https://www.pexels.com/photo/person-in-gray-button-up-
shirt-sitting-on-brown-wooden-chair-4107232/ [Accessed 21st
September 2010].
Cottonbro (2020). Round Table and White Table Cloth [image/jpeg]. Available at:
https://www.pexels.com/photo/round-table-and-white-table-cloth-3692887/
[Accessed 21st
September 2010].
Hesthaven, M. (2019). Woman taking picture of colourful sunset at sea [image/jpeg]. Available
at: https://unsplash.com/photos/xZM5sAsuib0 [Accessed 21st
September 2010].
Jeshoots.com (2017). Two Person Playing Sony Ps4. [image/jpeg]. Available at:
https://www.pexels.com/photo/blur-close-up-device-display-442576/ [Accessed 21st
September 2010].
Johnson, M. (2011). Crossword [online]. Flippity. Available at:
https://www.flippity.net/cw.php?k=1FAnTlZuj5Wxd--
k9Gqf5rNpT_QWZpuAt6sURA8s0Crk [Accessed 22nd
September 2020].
Karpouzis, K. (2016). Can machines read your emotions? TED Ideas worth spreading.
Available at:
https://www.ted.com/talks/kostas_karpouzis_can_machines_read_your_emotions/tra
nscript?language=en#t-29757 [Accessed 21st
September 2010].
Knight, A. (2019). High-Angle Photo of Robot. [image/jpeg]. Available at:
https://www.pexels.com/photo/high-angle-photo-of-robot-2599244/ [Accessed 21st
September 2010].
Pixabay (2016). Silver Security Camera. [image/jpeg]. Available at:
https://www.pexels.com/photo/silver-security-camera-207574/ [Accessed 21st
September 2010].
Shvets, A. (2020). Person Using Self Check in Kiosk [image/jpeg]. Available at:
https://www.pexels.com/photo/person-using-self-check-in-kiosk-3943949/ [Accessed
21st
September 2010].
Stem.T4L (2019). No title. [image/jpeg]. Available at: https://unsplash.com/photos/-
PnSpCHYKsw [Accessed 21st
September 2010].

16. 16
Subiyanto, K. (2020). Confident child removing clothes from washing machine. [image/jpeg].
Available at: https://www.pexels.com/photo/confident-child-removing-clothes-from-
washing-machine-4546167/ [Accessed 21st
September 2010].
ThisIsEngineering (2020). Female Engineer Working in Workshop. [image/jpeg]. Available at:
https://www.pexels.com/photo/female-engineer-working-in-workshop-3862632/
[Accessed 21st
September 2010].
UCLES (2018). A2 Flyers Wordlist picture book for exams from 2018. Available at:
https://www.cambridgeenglish.org/Images/351851-a2-flyers-word-list-2018.pdf
[Accessed 21st
September 2010].
UCLES (2019). Technology B1 Preliminary for Schools. Available at:
https://assets.cambridgeenglish.org/schools/b1-preliminary-posters.pdf [Accessed
21st
September 2010].