Bilgisayar (Bilimi) Eğitimi konusunda çok uzun zamandan bu yana görüşlerimi paylaşıyorum. Bizde bu konu ne yazık ki moda olarak gelip her modanın olduğu gibi demode olup hayatımızdan çıkıyor. Bu konunun öğretim programlarına girmesi sadece rapor yazarak gerçekleşmiyor. Aşağıdaki cümle yazıdan alıntı;
"İlk hizmet içi öğretmen eğitimleri Eylül 2025'te başlıyor."muş :-(
Konu çok boyutlu Fatih projesi sırasında karatahta üzerinde 32 saatlik öğretim programlarının başına ne geldiyse benzeri sonuçlar istemiyorsak bu işi iyi planlayıp adım adım sabırla yürütmeliyiz. Eğitimde değişimler süreçtir, bilgisayarda olduğu gibi "Run" deyince gerçekleşmez. Meraklısı için yazdıklarımın bir kısmını paylaşayım;
Not: Aynı çözüm kümesini kullanarak farklı sonuçlar beklemek konusunda A. Einstein'in sözü hep aklımda.
“It is not enough to know, it is necessary to be able to do it”
As in the advent of horseless carriages? Horseless carriage? In fact, the term reminded me of the term “wireless phone”, where terms like horseless carriage and cordless phone are situations where a new technology is compared to an old one by saying things that the new technology doesn’t have. After all, insisting on old technology in order to explain/accept new technology is a very old human habit. Against the cars that started mass production with Henry Ford’s production line idea, there were always those who made prescient comments such as “The horse is here to stay, but the automobile is only a novelty — a fad” and resisted innovation. It is not difficult to find similar predictions in every period of history and every innovation comes, for example; The paradox that “machines are coming to take our jobs” is an issue that has been around for hundreds of years, at least since the industrialization of weaving in the early 18th century, which increased productivity and feared that thousands of workers would be thrown out on the streets. The resulting displacement of workers is still a concern, as it was in the past.
In 1589, when Queen Elizabeth I of England applied for a royal patent for a knitting machine by the clergyman William Lee, she panicked and said: “Imagine what this invention will do to my poor subjects, if it were to happen it would surely ruin their lives by depriving them of employment.” In the 1880s, the Qing dynasty strongly opposed the construction of railways in China, arguing that losing their baggage-carrying jobs could lead to social upheaval. In the early 19th century, the Luddites sabotaged machinery to protect their business in England, despite the general economic growth fueled by steam power. Fears of robot-induced unemployment have always dominated the debate about future jobs. However, for some reason, these have not gone beyond wasting people’s time. Those who adapted quickly always took a step forward, while those who resisted had to continue to live with what was presented to them as slaves of their time by lamenting behind the fleeing trains. If we go back in time from today, it is possible to define periods in which more than one revolutionary change took place. Although there are many different definitions for these changes, the most widely accepted idea today is that we are in the “4th Industrial Revolution”. Unlike the previous three industrial revolutions, this period symbolizes a period in which human-robot relations developed a lot. The human-robot relationship is actually a form of the human-machine relationship, and there are many different human-machine relationship modes. While these are changes specific to this era, many innovations are excluded by people due to the typical human characteristic of “resistance to innovation”. The rapid change in technology makes it difficult to predict which job-specific skills will evolve and which will become obsolete in the near future. In the past, it took centuries for the shifts in skill requirements brought about by technological progress to manifest themselves. But in the digital age, advances in technology require new skills seemingly overnight. To give an example of the change in new skills, when we look at the advertisements for the same position in about 30 years;
Table: Socio-behavioral skills are becoming more important Job requirements of a Hilton Hotel manager candidate in Shanghai, China
1986
2018
Excellent character, willing to learn Between the ages of 20 and 25 Fluent English proficiency in good health Living close to the hotel location
Positive attitude and good communication skills Ability to work independently and as part of a team Proficient IT skills Have at least two years of experience, four-year university degree
Sources:
1986: Wenhui News, 17 August 1986, http://www.sohu.com/a/194532378_99909679; 2018: https://www.hosco .com/en/job/waldorf-astoria-shanghai-on-the-bund/management-trainee-front-office. Note: IT = Information Technology
We can see that three types of skills are becoming more and more important in place of the skills that were important in the last century. These are, respectively,
advanced cognitive skills, such as complex problem-solving,
socio-behavioural skills such as teamwork, and
combinations of skills that predict adaptability, such as reasoning and self-efficacy.
Since 2001, the share of employment in occupations with intensive non-routine cognitive and socio-behavioral skills has increased from 19 percent to 23 percent in developing economies and from 33 percent to 41 percent in advanced economies.
For a society formed by individuals with such skills, well-trained human resources and lifelong learning are required. That’s because individuals with more advanced skills are better able to take advantage of new technologies to adapt to the changing nature of work. Up to this point, I have tried to give examples of the effects of the carpet slipping from under our feet during the technology-human interaction on society. At the end of the day, lifelong education, education, has brought the result of well-educated people and their ability to adapt to the very rapid changes that occur in parallel with technological changes. In fact, the COVID-19 pandemic, which started all over the world in March 2020 and affected all societies, caused radical changes in education. The mass production paradigm of the industrial revolution, which was based on information transfer/loading, suddenly faced a major paradigmatic problem with the disappearance of the school base of this production system. Individuals who were prepared for life with the information overload that took place as 50 minutes of class and 10 minutes of break on production benches that were structured as classes that took shape parallel to the industrial revolution were actually not able to fully meet the requirements of this age. Otherwise, why would Koç, Sabancı and other industrial manufacturers have to establish their own schools and undertake the task of training suitable personnel for their own factories? If graduates of educational institutions today receive additional training to learn the job when they start working, the reason for this lies in the fact that today’s schools cannot train the individuals needed by the age. Today’s education system assumes that readiness for life is still in the formula “KNOWING is enough”. However, in this age, “Knowing is not enough, it is necessary to be able to do”. However, when we look at the undergraduate education programs (the latest Teacher Training Programs updated by the Council of Higher Education) in which teacher candidates who will play a very important role in raising the “Can Do Individuals” needed today are trained;
We see that the average theoretical course hours are 84.85% and the practice hours are 15.15%. In short, we aim to train teachers with whom we load knowledge. In fact, the numbers in this table give us enough clues as to why we cannot raise the individuals of the age. I will repeat a sentence I wrote above with a little modification “It is not enough to know, it is necessary to be able to do it, sorry for those who know, we hired Google and now there is Artificial Intelligence”. Yes, the developments in WEB have now made access to information (book information) unlimited by freeing it from a single format (text, sound, image, animation, simulation, etc.). Instead of wise people who impart knowledge as in schools before and after the industrial revolution, there is now a need for Learning Assistants (Guides) who will train individuals who have the knowledge, skills and attitudes to use this knowledge. In fact, most of the theoretical information given in the above table in all fields is far from meeting today’s needs.
When we look at current technological trends, we come across topics such as Artificial Intelligence and robots, Blockchain, Augmented Reality and Virtual Reality, Smart Applications (I – Applications), RPA (Robotic Process Automation), Big Data, Bioengineering, Clean energy, Mobility, WEB 3.0, Space technologies, Cloud and edge computing, New generation materials. Is there any need to say much about how much knowledge and practice the students received and practiced for these topics during the 12 years of Basic Education? The majority of the current trends listed above require technological knowledge, skills and attitudes. In short, can our teachers be given the technological training required by the age before they start their service? Again, if we look at the Teacher Training Undergraduate Programs on the pages of the Council of Higher Education;
Except for two programs, our teacher candidates take one technology-related course, and although the majority of these courses are given practically, they are not enough for them to acquire the Technological Formation, which is a requirement of the age. Again, we have come to the problem in the introductory parts of the article, in order to find teachers trained in accordance with the requirements of the age, it becomes necessary to give in-service trainings to teachers (to complete their deficiencies in undergraduate education).
When we delved into teacher training programs, we forgot about the big change; “COVID-19″, yes, this pandemic has caused huge changes in education/training systems. When the industrial revolution disabled schools, it became almost impossible to find solutions for education/training activities without using TECHNOLOGY. During the absolute closure periods, Parents and Teachers, who did not perceive the use of technology as keeping up with the times, were helpless in front of the students. There were other reasons for this, for example, although having the necessary technological devices appeared as a problem, the main problem was that teachers were not ready to use such virtual environments for education and training. As the first solution, the situation was tried to be passed by using presentation programs, which are indispensable for today’s classrooms and the biggest problem of the education system in my opinion. The method that confines the student-teacher relationship to the transmitter-listener mode in face-to-face education was transferred to virtual classroom environments without any changes during the COVID-19 period. This caused students to be more disconnected from the course. The multiple-choice exams created using the slides prepared for the presentation were very popular with the students because they completed many courses that they had not been successful in until this term by getting very high grades in these exams. In addition, schools with Technological Formation were able to close this term without suffering any loss of education/training in environments with classes and students and had the chance to prepare for and implement this new education/training paradigm. Now that schools have opened, a group of Ludist is again making statements such as the virtual environment is very harmful for our children. In fact, these COVID-19 absolute shutdowns herald the end of industrial revolution schools. As in the examples of horseless carriages and wireless phones, concepts such as virtual learning and distance learning will be hollow in the future and education will turn into a different form than today’s format. For example, the curriculum prepared with a 50-minute lecture and ten-minute break format to convey information will be replaced by curriculums, teaching methods, teaching materials in which more technology is used for education. In fact, the current slogan ” The future is coming” seems to be right for this change.
As a result, even if we are late for the question of what we should do next, we will have to say that wherever the damage is returned, it is profit, and we will have to make plans and put them into practice not only for teacher training but also for all professional fields. We should not forget that we need to train people who will perform all professions by having solid knowledge of the field (CK), professional knowledge (PK) that will enable them to use this field knowledge, and Technological Formation (TF) that will enable them to do this information using technology.
This excerpt from
“Aklımda Kalanlar” by Prof. Dr. M. Yaşar Özden explores the concept of a new
paradigm in education, suggesting it might be perceptionism. The
author discusses how societal changes brought about by technological
advancements, particularly the rise of artificial intelligence, are shifting
the focus from knowing and doing to how we perceive information.
The piece highlights the impact of the “post-truth” era and social media on
learning, suggesting that individuals’ perceptions, shaped by these
environments, are becoming the foundation for new forms of learning. It
contrasts this emerging paradigm with established learning theories like
behaviorism, cognitivism, and constructivism, arguing for a shift in how
education approaches information in this rapidly evolving landscape.
Briefing Document: A
New Paradigm in Education – Perceptionism
Source: Excerpts from “Eğitimde Yeni Paradigma:
Algıcılık olabilir mi? New paradigm in education: Could it be perceptionism –
Aklımda Kalanlar” by Prof. Dr. M. Yaşar Özden.
Date of Source: March 13, 2024
Author Background
(from source): Prof. Dr.
M. Yaşar Özden is a specialist in teacher education, distance education,
multimedia applications on the internet, web design and programming, and
currently focuses on Generative AI (GPT) applications in Education. He has a
strong background in adapting curricula to online spaces and is recognized in
science education and its impact on learning communities.
Main Themes:
The Impact of Technological Advancements
on Education: The
source argues that rapid technological changes, particularly the rise of
AI and the “post-truth” era, necessitate a fundamental shift in
educational paradigms.
The “Post-Truth” Era and its Educational
Implications: The
author highlights the significant impact of the post-truth era,
characterized by the prevalence of emotional and personal beliefs over
objective facts, on how information is consumed and perceived.
The Emergence of “Perceptionism” as a New
Learning Paradigm: The
core argument is that the traditional learning theories (Behaviorism,
Cognitivism, Constructivism) are insufficient to explain learning in the
current digital and post-truth environment, proposing “Perceptionism” as a
potential new paradigm.
The Shifting Nature of Schools and
Learning Environments: The
concept of the traditional physical school is being replaced by
distributed, digital learning environments, influenced by social media and
AI tools.
The Need for Critical Thinking and Media
Literacy: The author
emphasizes the critical importance of equipping students with skills to
navigate misinformation, evaluate information critically, and identify
manipulation in the post-truth landscape.
Most Important
Ideas and Facts:
Paradigm Shift is Inevitable: The author asserts that just as
industrial revolutions led to changes in societal paradigms and
consequently in education, the current technological revolution demands a
new educational paradigm.
From Knowing to Doing to Producing with
AI: The author
revises his earlier statement “Knowing is not enough, being able to do is
necessary,” acknowledging that AI tools like ChatGPT and Google Gemini
have taken over the “knowing” and much of the “doing.” The new emphasis is
on individuals using this readily accessible information to produce.
The Post-Truth Definition: The source provides a definition of
“Post-truth”: “Post-truth, objektif gerçeklik ve gerçeklikle
ilgili olguların, duygusal ve kişisel inançlardan veya ideolojik
görüşlerden daha az etkili olduğu bir durumu tanımlar” (Post-truth
is a term that defines a situation where objective reality and facts
related to reality are less influential than emotional and personal
beliefs or ideological views). It also notes that the increase in
information accessibility in the post-truth era is linked to a rise in
information pollution, misinformation, and manipulation, exacerbated by
social media.
Social Media’s Role in Shaping Perception: The author highlights how social
media facilitates the rapid spread of information, including fabricated
“truths,” which can be difficult to control and can lead to the formation
of new perceptions and potentially “non-learnings.”
Perceptionism Defined:“Algıcılık (Perceptionism)
yaklaşımında ise öğrenmeyi “algıdaki değişim” olarak tanımlayabiliriz.” (In
the Perceptionism approach, we can define learning as “change in
perception.”) This new paradigm suggests that learning in the post-truth
environment is fundamentally shaped by perceptions formed within the
social environment, independent of the individual.
Elements Influencing Learning in a
Perceptionist Environment:Active Engagement: Being an active user of social
networks.
Construction of Meaning: Individuals interpreting post-truth
perceptions formed in the social environment through their own experiences
and mental frameworks, integrating them into existing cognitive
structures.
Social Interaction: Social interaction is acknowledged
as important for co-constructing meaning, and in the context of the
post-truth environment, it can enhance the learning experience of
artificial realities.
The “My School in the Cloud” Concept: The traditional school concept is
being replaced by decentralized, digital learning environments (“My School
in the Cloud”) on social media, without geographical constraints, where
digital tools are widely used, and learning is time and place-independent.
Shift from Knowledge Acquisition to
Information Utilization for Production: Education is evolving towards individuals accessing
information instantly through AI tools and using this information to
become productive, rather than focusing on merely knowing or memorizing.
Outdated Educational Practices: The author suggests that traditional
methods like PowerPoint presentations and rote memorization for
multiple-choice questions are no longer sufficient in this new paradigm.
The Dual Nature of AI in Education: AI-powered environments have the
potential for both beneficial and undesirable outcomes in education.
Key Takeaways for
Educational Practice:
Educators need to acknowledge the profound
impact of the post-truth era and AI on how students perceive and learn.
The focus of education must shift from
knowledge transmission to developing critical thinking, media literacy,
and the ability to evaluate information critically.
Students need to be taught how to identify
misinformation and manipulation in the digital environment.
The potential of AI tools for positive
educational uses needs to be explored and leveraged.
Learning environments are becoming
increasingly digital and decentralized, requiring new approaches to
teaching and learning.
The ability to utilize readily available
information to produce new things is becoming more important than simply
knowing facts.
Quotes:
“Post-truth, objektif gerçeklik ve
gerçeklikle ilgili olguların, duygusal ve kişisel inançlardan veya
ideolojik görüşlerden daha az etkili olduğu bir durumu tanımlar.” (Post-truth is a term that defines a
situation where objective reality and facts related to reality are less
influential than emotional and personal beliefs or ideological views.)
“Post-truth dönemi, bilginin
erişilebilirliğinin artmasıyla birlikte, bilgi kirliliği, yanlış
bilgilendirme ve manipülasyonun da artmasıyla ilişkilendirilir.” (The post-truth period is associated
with the increase in information pollution, misinformation, and
manipulation as information accessibility increases.)
“Sosyal medyanın etkisiyle, bilgi ve
haberler hızla yayılabilir ve kontrol edilmesi zor olabilir, bu da
post-truth ortamının yayılmasına katkıda bulunur.” (With the effect of social media,
information and news can spread rapidly and be difficult to control, which
contributes to the spread of the post-truth environment.)
“Algıcılık (Perceptionism) yaklaşımında
ise öğrenmeyi “algıdaki değişim” olarak tanımlayabiliriz.” (In the Perceptionism approach, we
can define learning as “change in perception.”)
“Bilmek yetmez, Yapabilmek gerekir,
bilenler kusura bakmasın ChatGPT’yi (Google Gemini’yi vb.) işe aldık
şeklinde oldu.” (It
became “Knowing is not enough, being able to do is necessary, excuse those
who know, we hired ChatGPT (Google Gemini etc.).”)
“Artık bildiğimiz okul kavramının yerini
“Benim Okulum Bulutta” kavramı almakta…” (Now the concept of school as we know it is being replaced by
the concept of “My School in the Cloud”…)
This briefing document
summarizes the central arguments and significant points presented in the
provided source, emphasizing the author’s perspective on the need for a new
educational paradigm (“Perceptionism”) in response to the technological
advancements and the rise of the post-truth era.
Education in the
Post-Truth Era: Understanding Perceptionism
Study Guide
This study guide is
designed to help you review the concepts presented in the excerpt “Eğitimde
Yeni Paradigma: Algıcılık olabilir mi? New paradigm in education: Could it be
perceptionism – Aklımda Kalanlar” by Prof. Dr. M. Yaşar Özden. The excerpt
explores the evolving landscape of education in the context of technological
advancements, particularly artificial intelligence, and the emergence of a
“post-truth” era, proposing “perceptionism” as a potential new paradigm for
learning.
Key Concepts:
Paradigm: A term used to describe a worldview,
knowledge base, and a set of guidelines that determine how a group of
people thinks and behaves within a specific time frame. Paradigms change
in response to environmental shifts and the evolving meaning assigned to
life.
Industrial Revolutions: Significant historical periods
marked by major technological and societal changes that have profoundly
impacted life and consequently shifted existing paradigms.
Technological Advancements: The rapid development of
technologies like the Internet of Things, Web 3.0, Machine Learning, and
Artificial Intelligence, which are creating new questions and
possibilities in various aspects of life, including education.
Shift in Skill Emphasis: The transition from simply knowing
information to the necessity of being able to do things
with that information, especially with the advent of tools like ChatGPT
and Google Gemini.
Post-Truth Era: A period where objective facts and
reality are less influential in shaping public opinion and discourse than
emotional appeals, personal beliefs, and ideological perspectives. This
era is characterized by increased information pollution, misinformation,
and manipulation, exacerbated by the rapid spread of information through
social media.
Perceptionism (Algıcılık): Proposed as a potential new paradigm
in education, particularly relevant in the post-truth era. It is a
philosophical and psychological approach that focuses on how individuals
perceive, process, and interpret sensory information from their environment.
It emphasizes the role of individual perception, influenced by social
environment and the construction of meaning, as the basis for new
learning.
Perception: The process of processing and
interpreting sensory information received from the external world through
our sense organs. It allows us to notice and make sense of objects,
events, sounds, smells, and tactile sensations.
Evolution of Learning Theories: The excerpt traces the historical
progression of dominant learning theories in response to changing
paradigms:
Behaviorism: Learning is defined by observable
changes in behavior, assuming learning occurs independently of the
individual if the environment and materials are well-designed. Individual
differences and social interaction are secondary.
Cognitivism: Learning is defined as a change in
knowledge, comparing the mind to a computer that stores information in
short-term and long-term memory. Knowledge is seen as the same for
everyone, although personal differences exist, and social environment is
acknowledged.
Constructivism: Learning is defined as the
construction of meaning, which is entirely individual and influenced by
past knowledge and social environment. Social environment is emphasized as
highly influential in meaning-making.
Perceptionism: Learning is defined as a change in
perception. New learning is fundamentally based on perceptions formed
within the social environment, particularly in the post-truth context.
Factors Influencing Learning in
Perceptionism:Active Engagement: Active use of social networks.
Construction of Meaning: Individuals interpret post-truth
perceptions created in the social environment based on their own
experiences and mental frameworks, integrating them into existing
cognitive structures to form deeper understanding.
Social Interaction: Accepted as important in learning,
interaction with peers, teachers, and the wider community provides
opportunities for collaborative meaning-making and increases exposure to
artificial realities constructed in the post-truth environment.
Challenges of the Post-Truth Era for
Education: The
potential for AI-supported environments to be used for harmful purposes,
the erosion of critical thinking skills, the difficulty in accessing
accurate information, and the encouragement of emotionally or
ideologically driven decisions rather than evidence-based ones.
Importance of Media Literacy and Critical
Thinking: The need
to equip students with the skills to think critically, evaluate
information, identify misleading information, and recognize manipulation
tactics in the post-truth era.
“My School in the Cloud” (Benim Okulum
Bulutta): The
concept that the traditional idea of school is evolving into a paradigm
where learning occurs in virtual environments, free from the constraints
of physical location or time, utilizing various digital tools and AI.
Learning shifts from knowing information to accessing it instantly and
using it to produce.
Quiz
Answer the following
questions in 2-3 sentences each.
What is a paradigm and why are paradigm
shifts considered inevitable?
How have the industrial revolutions
impacted educational paradigms?
According to the author, how has the
emphasis in required skills shifted in the face of new technologies?
Define the “Post-Truth Era” as described
in the excerpt.
How does the rise of social media
contribute to the “Post-Truth Era”?
What is “Perceptionism” as proposed in the
excerpt?
Briefly explain how learning is defined in
the Behaviorist approach.
How does the Constructivist approach
differ from Behaviorism and Cognitivism in defining learning?
What is the primary factor influencing
learning in the Perceptionist approach?
Why is media literacy considered important
for students in the context of the post-truth era and perceptionism?
Essay Format Questions
Consider the following
questions for potential essay responses. Do not provide answers in this
section.
Analyze and evaluate the author’s argument
for “Perceptionism” as a new paradigm in education. How does it build upon
or depart from previous learning theories like Behaviorism, Cognitivism,
and Constructivism?
Discuss the implications of the
“Post-Truth Era” and the increasing use of artificial intelligence on the
role of the educator and the design of learning environments.
The author suggests that the traditional
concept of “school” is evolving into “My School in the Cloud.” Explore the
potential benefits and challenges of this shift towards digital and
AI-supported learning environments.
How can educational systems effectively
equip students with the critical thinking skills and media literacy
necessary to navigate the information landscape of the post-truth era?
Examine the relationship between social
interaction and the construction of meaning in the context of the proposed
Perceptionist paradigm. How might social media and AI tools influence this
interaction?
Glossary of Key Terms
Paradigma: A term used to describe a worldview,
knowledge base, and a set of guidelines that determine how a group of
people thinks and behaves within a specific time frame.
Endüstri Devrimleri (Industrial
Revolutions): Significant
historical periods marked by major technological and societal changes.
Nesnelerin İnterneti (Internet of Things –
IoT): The network of
physical objects—”things”—that are embedded with sensors, software, and
other technologies for the purpose of connecting and exchanging data with
other devices and systems over the internet.
WEB 3.0: The potential next phase of the internet, envisioned as a
decentralized web powered by blockchain technology, artificial
intelligence, and machine learning.
Makina Öğrenmesi (Machine Learning): A type of artificial intelligence
(AI) that allows software applications to become more accurate at
predicting outcomes without being explicitly programmed to do so.
Yapay Zeka (Artificial Intelligence – AI): The simulation of human intelligence
processes by machines, especially computer systems. These processes
include learning, reasoning, and self-correction.
Post-truth (Hakikat Sonrası Dönem): A situation where objective facts
are less influential in shaping public opinion than appeals to emotion and
personal belief.
Algıcılık (Perceptionism): A proposed new paradigm in
education, particularly relevant in the post-truth era, that focuses on
how individuals perceive, process, and interpret sensory information as
the basis for new learning, heavily influenced by social environment.
Algı (Perception): The process of processing and
interpreting sensory information received from the external world through
our sense organs, allowing us to notice and make sense of our
surroundings.
Davranışçı Yaklaşım (Behaviorism): A learning theory where learning is
defined by observable changes in behavior, focusing on the environmental
stimuli and behavioral responses.
Bilişselci Yaklaşım (Cognitivism): A learning theory where learning is
defined as a change in knowledge, focusing on mental processes like
memory, problem-solving, and information processing.
Oluşturmacı/Yapılandırmacı Yaklaşım
(Constructivism): A
learning theory where learning is defined as the construction of meaning,
emphasizing the active role of learners in building their own
understanding based on experiences and interactions.
Aktif Katılım (Active Engagement): Actively participating in
activities, particularly in the context of social networks in the
Perceptionist paradigm.
Anlamın İnşası (Construction of Meaning): The process by which individuals
build their own understanding and interpretation of information,
influenced by prior knowledge and experiences.
Sosyal Etkileşim (Social Interaction): The way people communicate and
interact with each other, considered important for collaborative learning
and meaning-making in the proposed paradigms.
Medya Okuryazarlığı (Media Literacy): The ability to access, analyze,
evaluate, and create media in a variety of forms.
Quiz Answer Key
A paradigm is a worldview and knowledge
base that determines how a group of people thinks and behaves within a
specific time frame. Paradigm shifts are considered inevitable because
they occur in response to changes in the environment and how people assign
meaning to their experiences.
The industrial revolutions have profoundly
impacted life through technological and production changes, leading to
necessary changes in human profiles and consequently bringing about
corresponding changes in education and teaching paradigms.
The author suggests that the emphasis has
shifted from simply knowing information to needing to be able to do things
with that information, especially now that AI tools can instantly access
knowledge.
The Post-Truth Era is a period where
objective facts are less influential than emotions, personal beliefs, and
ideological views in shaping public opinion and discourse.
Social media contributes to the Post-Truth
Era by facilitating the rapid spread of information, including
misinformation and manipulation, which can be difficult to control and can
quickly create and propagate new “realities” or perceptions.
Perceptionism is a proposed new paradigm
in education, particularly for the post-truth era, that suggests learning
is defined as a change in perception, heavily influenced by the social
environment and the construction of artificial realities.
In the Behaviorist approach, learning is
defined by observable changes in an individual’s behavior, assuming that
learning will occur independently of the individual if the learning
environment and materials are well-designed.
Constructivism differs by defining
learning as the individual construction of meaning, which is unique to
each person and heavily influenced by their past knowledge and social
environment, whereas Behaviorism focuses on observable behavior and
Cognitivism on internal knowledge storage.
The primary factor influencing learning in
the Perceptionist approach is the change in perception, which is shaped by
the social environment and the constructed realities within it,
particularly in the post-truth context.
Media literacy is considered important for
students in the post-truth era and the context of perceptionism because it
equips them with the skills to critically evaluate information, discern
accurate information from misinformation, and recognize manipulation
tactics prevalent in the current information landscape.
* You can use this framework for any target group/topic area where artificial intelligence is used.
The AI Competency Framework for Teachers highlights three key dimensions of AI in education: Learning with AI, Learning from AI, and Learning AI.
• Learning with AI refers to using AI-powered tools like adaptive learning platforms and chatbots to enhance student engagement and personalize learning experiences.
• Learning from AI involves leveraging AI-driven analytics to assess student performance, improve teaching strategies, and make data-informed decisions.
• Learning AI focuses on understanding AI technologies, ethical considerations, and teaching students about AI concepts such as machine learning and algorithms.
At the intersection of these three dimensions is the AI Competent Teacher (AICT)—a teacher who effectively integrates AI into teaching, learns from AI insights, and educates students about AI. This framework ensures educators are prepared to navigate AI-driven education, fostering both AI literacy and innovative teaching practices.
İlk örnek olarak “Eğitimde Üretken Yapay Zeka Kullanımı” konusunda UNESCO ve APRU raporlarını baz alan bir özel GPT hazırladım. Aşağıdaki resme tıklayarak kullanabilirsiniz.
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Benzeri yöntemi kullanarak belirli bir konuda özel GPT’ler oluşturup hedef kitlenizle paylaşabilirsiniz. Ben örnek olarak “Genel Biyoloji 101” dersi için bir özel GPT oluşturdum. Aşağıdaki resme tıklayarak kullanabilirsniz.
Aşağıdaki promptu girecek olusanız; “Hücre yapısıyla ilgili bana çoktan seçmeli, doğru yanlış, doldurmalı,, sürükle bırak olacak sekilde pratik problemler verebilir misin?”
Prompt: hücre organellerini gösteren üç boyutlu bir imaj oluşturabilir misin?
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“Bilmek yetmez, yapabilmek gerekir. bilenler kusura bakmasın ChatGPT’yi işe aldık” diyerek bitireyim.
Prof. Miller’s Lecture Notes: Photoelectric Effect
Mart 12, 2025
OpenAI Edu tarafından duyurulan yeni bir paylaşımı çok faydalı bulduğum için paylaştım. İlgili sayfa için aşağıdaki ekran görüntüsüne tıklayabilirsiniz.
Bu örnekte ders sırasında çekilen bir karatahta görüntüsü üzerinden yapılabilecekler anlatılmış. Aslında hikaye ChatGPT promptunda gizli;
“Profesör Miller’ın fizik derslerine geç kaldım ve dersin bu kısmını kaçırdım. Bana bunu açıklayabilir misiniz?”
Prof. Miller’in Fizik Ders Notları
Ağanın eli tutulmaz diyerek Yapay Zeka kullanarak ben neler yapabilirim diye yola çıkınca önce bir podcast yaptım bu başlık için;
Sonra hazır başlamışken daha neler yapabilirim diye uğraşınca ortaya bayağı detaylı bir doküman çıktı.
Prof. Miller’s Lecture Notes: Photoelectric Effect
Professor Miller’s lecture notes on the photoelectric effect are presented on a chalkboard. The notes describe the phenomenon where light incident on a material can eject electrons, detailing key concepts like photons, their energy (E=hf), and the work function (Φ). The relationship between kinetic energy of emitted electrons (Kmax) and the frequency of light is also illustrated with a graph, showing the threshold frequency and stopping potential.
Briefing Document
This briefing document summarizes the main themes, important ideas, and key formulas presented in the provided image of Professor Miller’s lecture notes. The notes primarily focus on the photoelectric effect, its theoretical explanation using photons, and related graphical representations.
Main Themes:
The Photoelectric Effect: The notes clearly define and describe the photoelectric effect, highlighting the emission of electrons from a metal surface when light shines on it.
“The Photoelectric Effect: Light shines on metal surface -> electrons are emitted.”
The notes emphasize that the kinetic energy of the emitted electrons depends on the frequency (and therefore energy) of the incident light, not its intensity.
“K.E. of emitted e- depends on frequency of light (not intensity).”
The existence of a threshold frequency (f₀) below which no electrons are emitted, regardless of intensity, is a crucial point.
“There exists a threshold frequency (f₀) below which no electrons are emitted (regardless of intensity).”
Einstein’s Photon Model: The lecture introduces Einstein’s explanation of the photoelectric effect, which posits that light consists of discrete packets of energy called photons.
“Einstein’s Photon Model: Light consists of photons (packets of energy).”
The energy of a photon (E) is directly proportional to its frequency (f), with Planck’s constant (h) as the constant of proportionality.
“Photon energy: E = hf”
This model explains the threshold frequency by stating that a minimum amount of energy (work function, Φ) is required to eject an electron from the metal surface.
“Work function: Φ = hf₀ = minimum energy needed to eject e-“
The Photoelectric Equation: The notes present the fundamental equation governing the photoelectric effect, relating the kinetic energy of emitted electrons to the photon energy and the work function.
“K.E.max = hf – Φ”
This equation underscores the linear relationship between the maximum kinetic energy of the emitted electrons and the frequency of the incident light.
Graphical Representation of the Photoelectric Effect: The lecture uses a graph of stopping potential (Vs) versus frequency (f) to illustrate the key relationships.
The graph shows a linear relationship with a positive slope.
“Stopping Potential vs. Frequency (f)” is the title of the graph.
The slope of the graph is related to Planck’s constant divided by the elementary charge (e).
“Slope = h/e”
The x-intercept of the graph represents the threshold frequency (f₀).
“x-intercept = f₀”
The y-intercept (extrapolated) is related to the negative of the work function divided by the elementary charge (-Φ/e).
“y-intercept = -Φ/e”
Stopping Potential: The concept of stopping potential (Vs) is introduced as the potential difference required to stop the most energetic emitted electrons.
“Stopping Potential (Vs): Potential needed to stop the most energetic e-.”
The relationship between stopping potential and maximum kinetic energy is given as:
“eVs = K.E.max”
Important Notes and Observations: The notes also include key observations and implications of the photoelectric effect.
“Note: The increased intensity means more photons (higher current), but not higher energy (K.E.max).” This reinforces the idea that intensity affects the number of emitted electrons (current), while frequency affects their kinetic energy.
“The theory shows that light behaves like particles (photons) in this case.” This highlights the wave-particle duality of light.
“Light interacts with matter and transfers energy in discrete packets (quanta).” This emphasizes the quantized nature of light energy transfer.
Most Important Ideas and Facts:
The photoelectric effect demonstrates that light can behave as particles (photons) with discrete energy packets.
The energy of a photon is directly proportional to its frequency (E = hf).
A minimum energy (work function, Φ) is required to eject an electron from a metal surface.
The maximum kinetic energy of emitted electrons depends linearly on the frequency of incident light (K.E.max = hf – Φ).
There exists a threshold frequency below which no photoelectrons are emitted, regardless of light intensity.
Light intensity affects the number of emitted electrons (photocurrent) but not their maximum kinetic energy.
The stopping potential is a measure of the maximum kinetic energy of the emitted electrons (eVs = K.E.max).
Graphical analysis of stopping potential versus frequency provides a way to determine Planck’s constant, the work function, and the threshold frequency.
Quotes from Original Sources:
“The Photoelectric Effect: Light shines on metal surface -> electrons are emitted.”
“K.E. of emitted e- depends on frequency of light (not intensity).”
“There exists a threshold frequency (f₀) below which no electrons are emitted (regardless of intensity).”
“Einstein’s Photon Model: Light consists of photons (packets of energy).”
“Photon energy: E = hf”
“Work function: Φ = hf₀ = minimum energy needed to eject e-“
“K.E.max = hf – Φ”
“Stopping Potential (Vs): Potential needed to stop the most energetic e-.”
“eVs = K.E.max”
“Note: The increased intensity means more photons (higher current), but not higher energy (K.E.max).”
“The theory shows that light behaves like particles (photons) in this case.”
“Light interacts with matter and transfers energy in discrete packets (quanta).”
“Stopping Potential vs. Frequency (f)” (Graph title)
“Slope = h/e” (Graph characteristic)
“x-intercept = f₀” (Graph characteristic)
“y-intercept = -Φ/e” (Graph characteristic)
This briefing document provides a concise overview of the key concepts related to the photoelectric effect as presented in Professor Miller’s lecture notes. The notes effectively combine definitions, theoretical explanations, mathematical formulas, and graphical representations to convey a comprehensive understanding of this fundamental phenomenon in physics.
Quantum Physics Review Guide
Quiz
Describe the photoelectric effect in your own words. What key observation about the emitted electrons puzzled classical physicists?
According to the notes, what is the relationship between the energy of a photon and its frequency? Write down the relevant equation and identify each variable.
What does the work function (Φ) represent in the context of the photoelectric effect? How does it relate to the kinetic energy of emitted electrons?
Explain the concept of the threshold frequency (f₀). What happens if the frequency of incident light is below this threshold?
Describe the relationship depicted in the “Photoelectric Effect Graph.” What do the x-axis and y-axis represent, and what is the significance of the slope?
What does the stopping potential (V_s) signify in a photoelectric effect experiment? How is it related to the maximum kinetic energy of the emitted electrons?
According to the “Millikan’s Oil Drop Experiment” notes, what two forces were balanced on the charged oil drop? What was the purpose of this experiment?
What is the fundamental charge of an electron, as determined by Millikan’s oil drop experiment (as shown in the notes)? What symbol is used to represent this charge?
Explain the concept of quantization of charge as evidenced by Millikan’s experiment. Why was this a significant finding?
According to the notes on “Classical Theory vs. Observation,” what was the classical prediction regarding the intensity of light and the kinetic energy of emitted electrons in the photoelectric effect? How did experimental observations contradict this prediction?
Quiz Answer Key
The photoelectric effect is the phenomenon where electrons are emitted from a material’s surface when light of a sufficient frequency shines on it. Classical physics expected that the kinetic energy of emitted electrons would depend on the intensity of the light, but observations showed it depended on the frequency.
The energy of a photon is directly proportional to its frequency. The equation is E = hf, where E is the photon energy, h is Planck’s constant, and f is the frequency.
The work function (Φ) is the minimum energy required to remove an electron from the surface of a particular metal. The maximum kinetic energy (K_max) of the emitted electrons is equal to the photon energy minus the work function: K_max = hf – Φ.
The threshold frequency (f₀) is the minimum frequency of incident light required to eject electrons from a metal surface. If the frequency of light is below f₀, no electrons will be emitted, regardless of the light’s intensity.
The “Photoelectric Effect Graph” plots the stopping potential (V_s) on the y-axis against the frequency (f) of the incident light on the x-axis. The slope of this graph is Planck’s constant (h/e), and the x-intercept represents the threshold frequency (f₀).
The stopping potential (V_s) is the reverse voltage required to stop the most energetic emitted electrons from reaching the collector in a photoelectric effect experiment. The maximum kinetic energy of the emitted electrons is related to the stopping potential by the equation K_max = eV_s, where e is the elementary charge.
In Millikan’s oil drop experiment, the electric force (due to the electric field applied between the plates) and the gravitational force were balanced on a charged oil drop. The purpose of this experiment was to determine the fundamental unit of electric charge (the charge of a single electron).
According to the notes, the fundamental charge of an electron (e) is approximately 1.602 x 10⁻¹⁹ Coulombs. The symbol used to represent this charge is ‘e’.
Millikan’s experiment showed that the charge on each oil drop was always a whole number multiple of the elementary charge (e). This demonstrated that electric charge is quantized, meaning it exists in discrete units rather than continuous amounts.
Classical theory predicted that the kinetic energy of emitted electrons in the photoelectric effect should increase with the intensity of the incident light and that electrons should be emitted regardless of the frequency, provided the light was intense enough. Observations showed that kinetic energy depended on frequency, and there was a threshold frequency below which no electrons were emitted.
Essay Format Questions
Discuss the significance of the photoelectric effect experiment in the development of quantum mechanics. How did it challenge classical wave theory of light, and what key concepts were introduced to explain the observed phenomena?
Explain the principles behind Millikan’s oil drop experiment and how the results of this experiment provided crucial evidence for the quantization of electric charge. Discuss the implications of this finding for our understanding of matter and electricity.
Compare and contrast the predictions of classical physics and the experimental observations of the photoelectric effect. Analyze the shortcomings of classical theory in explaining this phenomenon and how Einstein’s explanation resolved these discrepancies.
Describe the relationship between photon energy, work function, and the kinetic energy of emitted electrons in the photoelectric effect. Explain how the concepts of threshold frequency and stopping potential are related to these quantities and how they can be experimentally determined.
Discuss the impact of the photoelectric effect and the quantization of charge on subsequent developments in physics. How did these discoveries pave the way for further understanding of atomic structure and the behavior of light and matter at the quantum level?
Glossary of Key Terms
Photoelectric Effect: The emission of electrons from a material when light of a sufficient frequency shines on it.
Photon: A quantum of electromagnetic radiation, considered as a discrete packet of energy that behaves like a particle. Its energy is proportional to its frequency (E = hf).
Work Function (Φ): The minimum amount of energy required to remove an electron from the surface of a particular solid material.
Threshold Frequency (f₀): The minimum frequency of incident light that can cause photoemission of electrons from a given metal surface. Light with a frequency below this value will not eject electrons, regardless of its intensity.
Planck’s Constant (h): A fundamental physical constant that relates the energy of a photon to its frequency. Its approximate value is 6.626 x 10⁻³⁴ joule-seconds.
Kinetic Energy (K_max): The energy of motion of the emitted electrons in the photoelectric effect. The maximum kinetic energy is given by K_max = hf – Φ.
Stopping Potential (V_s): The minimum retarding potential applied to the collector plate in a photoelectric effect experiment that is just sufficient to stop the most energetic emitted electrons from reaching it. It is related to the maximum kinetic energy by K_max = eV_s.
Elementary Charge (e): The magnitude of the electric charge carried by a single proton or electron. Its approximate value is 1.602 x 10⁻¹⁹ Coulombs.
Quantization of Charge: The principle that electric charge exists only in discrete integer multiples of the elementary charge.
Millikan’s Oil Drop Experiment: A classic physics experiment performed by Robert Millikan and Harvey Fletcher in 1909 to determine the elementary electric charge (the charge of the electron).
Frequently Asked Questions
Q1: What is the photoelectric effect, as described in the lecture notes?
The photoelectric effect is a phenomenon where electrons are emitted from a material’s surface (typically a metal) when light of sufficient frequency shines on it. The lecture notes highlight that this effect demonstrates that light can behave as particles (photons), where the energy of each photon is proportional to its frequency. The key aspects mentioned are the incident light causing electron ejection and the dependence on the light’s frequency, not just its intensity.
Q2: How is the energy of a photon related to its frequency and wavelength, according to the lecture notes?
The lecture notes provide the fundamental equation relating a photon’s energy (E) to its frequency (f): E = hf, where ‘h’ is Planck’s constant. Additionally, since the speed of light (c) is related to frequency and wavelength (λ) by c = fλ, the energy of a photon can also be expressed in terms of wavelength as E = hc/λ. These equations are central to understanding the quantum nature of light and its interaction with matter in the photoelectric effect.
Q3: What is the work function (Φ) of a metal in the context of the photoelectric effect?
The work function (Φ) is the minimum energy required to remove an electron from the surface of a particular metal. It’s an intrinsic property of the material. In the context of the photoelectric effect, a photon must have energy (hf) equal to or greater than the work function for an electron to be ejected. Any excess energy beyond the work function will be transferred to the emitted electron as kinetic energy.
Q4: How is the maximum kinetic energy (K.E.max) of the emitted electrons related to the incident light’s frequency and the metal’s work function?
The lecture notes present Einstein’s photoelectric equation: K.E.max = hf – Φ. This equation states that the maximum kinetic energy of the emitted electrons is equal to the energy of the incident photon (hf) minus the work function (Φ) of the metal. This implies that there is a threshold frequency (f₀ = Φ/h) below which no electrons will be emitted, regardless of the light’s intensity. Above this threshold, the kinetic energy of the emitted electrons increases linearly with the frequency of the incident light.
Q5: What does the provided graph likely represent in the context of the photoelectric effect?
The sketch of a graph with axes labeled “V_stop” (stopping potential) on the y-axis and “f” (frequency) on the x-axis, showing a straight line with a positive slope and a y-intercept on the negative y-axis, likely represents the relationship between the stopping potential required to halt the emitted electrons and the frequency of the incident light. The slope of this graph is equal to h/e (Planck’s constant divided by the elementary charge), and the x-intercept represents the threshold frequency (f₀), while the y-intercept (when extrapolated) relates to the work function (Φ = -eV₀, where V₀ is the stopping potential at zero frequency).
Q6: What is the significance of the stopping potential (V_stop) in a photoelectric effect experiment?
The stopping potential (V_stop) is the minimum reverse potential difference applied between the anode and cathode in a photoelectric effect experiment that is just sufficient to stop the most energetic emitted electrons from reaching the anode, causing the photocurrent to drop to zero. The kinetic energy of the most energetic electrons (K.E.max) is related to the stopping potential by the equation K.E.max = eV_stop, where ‘e’ is the elementary charge. Measuring the stopping potential for different frequencies of incident light allows for the determination of Planck’s constant and the work function of the material.
Q7: According to the notes, what was a classical expectation about the photoelectric effect that was contradicted by experimental observations?
The lecture notes mention that classically, it was expected that the kinetic energy of the emitted electrons should increase with the intensity (brightness) of the incident light. However, experiments showed that the kinetic energy of the emitted electrons depends on the frequency of the light, not its intensity. Increasing the intensity only increases the number of emitted electrons (and thus the photocurrent), but not their maximum kinetic energy. This discrepancy between classical predictions and experimental results was a key reason for the development of the quantum theory of light.
Q8: What key takeaway message about the nature of light is emphasized by the photoelectric effect, as suggested by the lecture notes?
The photoelectric effect strongly supports the idea that light has a dual nature, exhibiting both wave-like and particle-like properties. While phenomena like diffraction and interference are explained by the wave nature of light, the photoelectric effect can only be adequately explained by considering light as consisting of discrete packets of energy called photons. The energy of these photons is quantized and directly proportional to the frequency of the light, demonstrating the particle aspect of electromagnetic radiation.
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