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AI in Mathematics: The Revolution in Scientific Writing

Artificial Intelligence (AI) is a field of computer science that seeks to develop systems able to perform tasks that traditionally require human intelligence, such as logical reasoning, problem solving, and learning. Based on advanced algorithms and machine learning models, AI can analyze large volumes of data, identify complex patterns and adapt autonomously to new contexts.

In mathematics, these capabilities are transforming the way knowledge is generated, verified, and communicated. From automating demonstrations to generating detailed explanations, AI is facilitating the work of researchers, teachers, and students. In addition, its ability to process natural language is improving the writing of mathematical papers, making texts more accessible, accurate and structured.

In this article, we will explore how AI in math is revolutionizing mathematical writing and how Wiris’ tools are part of this advancement.

The Role of AI in math and the Creation and Editing of Mathematical Content

Writing scientific papers in mathematics has always been a challenge due to the complexity of their notations and symbols. Traditionally, mathematicians have relied on handwriting or the use of complex typesetting languages. However, with the advent of AI, the process of creating and editing scientific documents has evolved exponentially.

Artificial intelligence has brought multiple benefits to the writing of mathematical papers, facilitating both the writing and the editing and publication of academic papers. Below are some of the main ways in which AI is impacting this area.

Handwriting recognition

One of the most significant advances has been the development of systems capable of interpreting and digitizing handwritten notes. Traditionally, mathematicians wrote their equations and proofs on paper, which was time-consuming if they needed to transcribe them into a digital format. With AI-based handwriting recognition tools, such as those built into MathType, it is now possible to directly handwrite equations into our touch devices and automatically convert them into editable digital text.

This not only saves time but also reduces transcription errors and allows you to work more efficiently. In addition, this type of technology is especially useful for students and teachers, as it facilitates the conversion of notes into organized documents without the need for manual typing. 

Formula automation

In the creation of mathematical articles, writing formulas accurately is essential. Traditionally, this required specialized tools that, while powerful, could be complex and demanded a deep understanding of their syntax and structure, such as LaTex.  

Advancements in technology have enabled the development of tools like MathType, which simplify equation writing without the need for coding. Instead of memorizing commands and code structures, users can simply enter their formulas through an intuitive graphical interface. This democratizes access to mathematical writing, allowing more people, regardless of their technical expertise, to create high-quality mathematical documents.  

Another key aspect is the automatic correction of errors in equations. AI in math can identify inconsistencies in formula writing and suggest real-time corrections, preventing mistakes that could compromise the validity of an academic paper.

Optimization of editing

Another benefit that AI has brought is the optimization of the editing of mathematical documents. In the past, mathematicians and scientists had to manually check their documents for errors in equations, notation and text structure. Today, there are AI algorithms embedded in editing programs that can analyze the consistency of mathematical expressions, suggest improvements in writing and detect inconsistencies.

AI-based writing assistants, such as those integrated into advanced text processors, can help improve the clarity and readability of mathematical articles. In addition, they provide stylistic recommendations to give the paper a logical and easy-to-follow structure, which is crucial in academic paper writing.

The integration of AI into mathematical writing is not just an evolution but a revolution that is transforming the way we create, edit, and share scientific knowledge. Tools like Wiris, with their powerful capabilities, are making mathematical writing more accessible, efficient, and error-free. As these technologies continue to advance, they will further bridge the gap between human intuition and machine accuracy, making the work of researchers, teachers, and students alike easier. If you found this exploration interesting, share it with your peers and join the conversation about the future of AI in math.

If you’d like to find out more about our products, please feel free to get in touch with our Sales team at sales@wiris.com for more information.

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Wiris in the Classroom: Learn and Practice with Unlimited Exercises

Learning mathematics requires more than just understanding theories: the key to mastering complex concepts and honing skills lies in continuous practice. However, traditional methods often limit the learning process: once the student has solved a problem, the challenge disappears, and exams often repeat the same questions, thus losing their value as an assessment tool. Imagine having the possibility to generate unlimited exercises with random variables, adapted to the needs of each student. With Wiris, this is now possible.

In addition, it has an automatic correction functionality which means that while the exercise is being generated, the answer is calculated simultaneously. This allows instant feedback, making it easier to learn and correct mistakes immediately.
For teachers, this tool offers a key advantage: the possibility of generating an infinite number of exercises, with each one being unique. In this way, teachers can create varied and personalized learning experiences, ensuring that students face new challenges every time they practice.

For their part, students enjoy constant practice which allows them to reinforce their skills without the worry of repeating the same exercises. In addition, this ability to generate unlimited exercises gives them excellent preparation for exams.

Practical example: Solving a system of linear equations

To illustrate how this tool works and how it can be used in the classroom, we will focus on solving systems of linear equations. We chose these types of problems because they represent a common mathematical challenge faced by all students and offer the possibility to explore different problem-solving methods. In addition, systems of equations can have various characteristics, such as being compatible, incompatible, or indeterminate, allowing students to work with a wide range of situations.

Let us imagine that we have the following system of linear equations with three unknowns:

We are going to solve it using Gauss’s Method. The first step is to write the system in the form of an augmented matrix: 

Now, we will apply elementary operations to reduce the matrix to its row echelon form.

Therefore, we obtain: 

From equation 3 of the system, we find the variable z:

Unlimited generation of systems of linear equations with random variables

Now that we have solved this system, for further practice, we would like to be able to generate new systems of equations of the same form but with random values.

These systems would take the following form:

Below, we will show you a code example to implement this functionality and generate given random systems of equations. With Wiris, it is totally possible!

r() := random(-4,4)

sol = [r() with i in 1..3]

[a,b,c] = sol

repeat 

A = [[r() with i in 1..3] with j in 1..3]

until determinant (A) != 0 

b = A * sol

ec = {}

for i in 1..3 do

ecaux = A.i * [x,y,z]

ec = append(ec, ecaux = b.i)

end

{ec1, ec2, ec3} = ec

r() := random(-4,4): This function generates a random number between -4 and 4.

sol = [r() with i in 1..3]: Here, three random values are generated that will represent the solutions of the system of equations.

[a,b,c] = sol: The generated values are assigned to the unknowns of the system.

repeat…until determinant(A) != 0: This block ensures that the coefficient matrix A is invertible (i.e., its determinant is not zero), which guarantees the system has a unique solution.

b = A * sol: The result vector b is calculated by multiplying the coefficient matrix A by the solutions sol

for i in 1..3 do: In this cycle, the three equations are generated, using each of the rows of the matrix A and the solutions sol.

{ec1, ec2, ec3} = ec: Finally, the three generated equations are stored in the variables ec1, ec2, and ec3, ready to be used in new exercises.

Using WirisQuizzes and implementing this code as a question, we can obtain the following results:

Reloading another system with the symbol “=” generates a new set of equations, as shown below:

For more details, you can consult the complete product documentation here.

If you have found this article useful, we would love you to share it with other colleagues, teachers or students. We would also be delighted to hear your opinion and any suggestions you may have.

 

Check Out WirisQuizzes

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Gamification in Math Learning: Does it Improve Learning?

Teenager playing learning

Gamification in Math Learning: Benefits & Challenges

Struggling to keep students engaged? Gamification, the use of game mechanics in learning, helps increase motivation, comprehension, and retention. The abstraction of concepts and the difficulty in linking them to real-life situations can generate disinterest, frustration and even anxiety in students. In this context, gamification has emerged as an innovative strategy that aims to transform the learning experience by integrating game elements into the educational process.

But what exactly is gamification, and what impact does it have on the teaching of mathematics? According to Deterding et al. (2011), it is defined as the use of game design elements in non-game contexts to enhance the participation, motivation, and engagement of individuals. In the educational setting, this involves not only the incorporation of game mechanics such as challenges, immediate feedback, points, and rewards, but also the creation of more dynamic and interactive experiences that encourage exploration and active learning.

Throughout this article, we will explore the existing evidence on the effectiveness of gamification in math education and see how interactive games like LearningLemur can benefit students’ learning.

Why Gamification Works: Key Benefits for Math Learning

Gamification has proven to be an effective tool for improving the learning experience in various disciplines, and mathematics is no exception. Its impact goes beyond making classes more entertaining; it influences key aspects such as motivation, understanding of concepts, and the development of cognitive and social skills. Below are some of the main benefits supported by research.

Increased Motivation and Engagement

One of the main challenges in teaching mathematics is to maintain students’ interest, especially when they perceive the exercises as repetitive or difficult. Gamification transforms these tasks into interactive and stimulating experiences. According to a study by Hamari, Koivisto, and Sarsa (2014), the implementation of gamified strategies has been shown to significantly increase motivation and academic performance in various disciplines, including mathematics.

Improved Comprehension and Retention of Concepts

 

Games allow students to interact with mathematical concepts in a hands-on, visual way, facilitating deeper understanding. Instead of memorizing formulas without context, students can experiment with problems in dynamic scenarios. A study by Wouters et al. (2013) indicated that gamified environments not only improve knowledge retention but also strengthen the ability to apply what is learned in different situations. 

Cognitive and Social Skills Development

Beyond learning mathematical concepts, gamification promotes essential skills for critical thinking and problem-solving. Solving challenges within a gamified environment requires students to analyze situations, explore different strategies, and adapt their approach based on the results obtained. In addition, many gamified experiences include collaborative dynamics that foster communication and teamwork. It also encourages resilience by allowing students to learn from their mistakes without the fear of conven

tional academic failure.

Mathematics Anxiety Reduction

Math anxiety is a common problem that can affect students’ performance and attitude toward the subject. Presenting problems in a playful and less structured format can reduce the pressure associated with formal learning. According to Sailer et al. (2017), gamification helps to generate a more positive relationship with mathematics, allowing students to face challenges without fear of failure. Immediate feedback and reward systems reinforce individual progress, helping to build confidence and autonomy in learning.

Gamification Challenges: What Educators Need to Know 

While gamification offers multiple benefits in mathematics learning, its effectiveness depends largely on how it is designed and implemented. Some key factors to consider for successful implementation are:

  • Designing appropriate content: Creating gamified activities aligned with curricular objectives requires time and planning on the part of educators.
  • Balancing Play and Learning: It is essential that the fun of the game does not overshadow the educational content, ensuring that students acquire the intended mathematical skills. To avoid this problem, it is key to design activities where progress in the game depends on mastery of the mathematical concepts, ensuring that the mechanics reinforce the content rather than distract from it.
  • Adaptability: Each student learns at their own pace and in a different way. An effective gamified approach must be flexible and allow for customization according to learners’ skill levels and learning styles.

Strategies for Effective Gamification in Mathematics Learning

To maximize the potential of gamification in math, educators and developers must carefully structure their approach. Here are some key strategies to ensure effective implementation:

Setting Clear Learning Objectives

Gamification must have a clear educational purpose to be effective. Before incorporating game elements, it is essential to define precise learning outcomes. Every challenge, reward, or interactive element should directly contribute to developing students’ understanding of mathematical concepts. When games are designed to align with curriculum goals, students remain engaged while making measurable academic progress.

Incorporating Interactive Games for Engagement

Engaging students through interactive math learning is one of the most effective ways to enhance learning. Digital platforms and apps provide adaptive learning experiences that offer students challenges suited to their individual skill levels. Features such as leaderboards, badges, and achievements create a sense of accomplishment, motivating students to persist in solving mathematical problems while reinforcing key concepts.

Providing Instant Feedback and Progress Tracking

Timely feedback is crucial in the learning process. One of the major advantages of gamification in math learning is the ability to provide instant feedback. When students receive immediate results on their performance, they can quickly identify mistakes, adjust their approach, and strengthen their understanding. Many digital platforms include progress-tracking tools, allowing both students and educators to monitor learning trends, address weaknesses, and celebrate achievements.

Encouraging Collaboration and Healthy Competition

Gamified learning is not just about individual progress—it can also foster teamwork and social interaction. Incorporating cooperative challenges and team-based problem-solving enhances mathematics learning by encouraging peer-to-peer discussions and shared strategies. At the same time, friendly competition through scoreboards and ranking systems can inspire students to push themselves further, increasing motivation and engagement in a healthy, constructive way.

Tools and Resources for Gamifying Mathematics Learning

With advancements in technology, numerous tools are available that support gamification in math. These resources offer diverse ways to create a more dynamic learning experience, helping students grasp mathematical concepts more effectively:

  • Digital Learning Platforms: Websites and apps that integrate math practice with games to teach mathematical concepts through fun and challenging activities.
  • Classroom Gamification Kits: Both physical and digital resources are designed to help teachers implement game-based learning strategies in their lessons.
  • Virtual and Augmented Reality: Immersive experiences that provide students with visual and hands-on interactions to better understand abstract mathematical ideas.
  • Customizable Gamification Plugins: LMS-integrated tools that allow educators to personalize their teaching by adding game-based elements to their curriculum.

Try Gamification in Mathematics Learning with Learning Lemur

The benefits of gamification in mathematics learning are clear: increased motivation, improved comprehension, and enhanced engagement. If you’re ready to experience the power of interactive games in education, explore Learning Lemur. Our platform allows educators and students to immerse themselves in engaging, game-based mathematics learning experiences.

Create a free account today and discover how gamification can revolutionize the way you learn mathematics!

Start Using Gamification for Free

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What is the Collatz Conjecture?

What is the Collatz Conjecture?

Mathematical conjectures are riddles that challenge the human mind: seemingly simple problems that, despite having been verified in millions of cases, still lack a proof. They are seemingly intuitive questions that hide unexpected complexity. 

The fascinating thing about conjectures is that, in many cases, they can be empirically verified i.e., verified by an enormous number of numerical examples. However, this verification does not satisfy mathematicians, who seek a theoretical proof, a solid proof that validates the statement in its entirety. Without such a proof, the conjectures remain open challenges. 

The Collatz conjecture is a perfect example of this type of mathematical mystery. It was proposed in 1937 by Lothar Collatz and its statement is as follows: 

Choosing any positive integer we will apply the following steps: 

➔ If the number is even, we will divide it by 2. 

➔ If the number is odd, multiply it by 3 and then add 1. 

➔ Repeat the process with the new number obtained. 

The conjecture says that, no matter what number you start with, you will always get to number 1. Once you get to 1, the process repeats indefinitely: 1 →4 →2 →1

Formally, this can be written as the function f=N →N defined as

Two illustrative examples of the Collatz Conjecture

Let’s look at a couple of simple examples.

Let’s take the number n=6 and apply the steps of the Collatz conjecture:

  1. 6 is even so we divide by 2: 6/2=3
  2. 3 is odd so we multiply by 3 and add 1: 3·3+1=10
  3. 10 is even so we divide by 2: 10/2=5
  4. 5 is odd so we multiply by 3 and add 1: 3·5+1=16
  5. 16 is even so we divide by 2: 16/2=8
  6. 8 is even so we divide by 2: 8/2=4
  7. 4 is even so we divide by 2: 4/2=2
  8. 2 is even so we divide by 2: 2/2=1

Once we reach 1, the process is repeated: 1 →4 →2 →1.

So we observe that starting with n=6 the conjecture is satisfied.

Let us now take the number n=21 and apply the steps of the Collatz conjecture:

  1. 21 is odd so we multiply by 3 and add 1: 21·3+1=64
  2. 64 is even so we divide by 2: 64/2=32
  3. 32 is even so we divide by 2: 32/2=16
  4. 16 is even so we divide by 2: 16/2=8
  5. 8 is even so we divide by 2: 8/2=4
  6. 4 is even so we divide by 2: 4/2=2
  7. 2 is even so we divide by 2: 2/2=1

Again, we arrive at number 1.

Both examples have reached the number 1, but in a different number of steps. In fact, although 21 is a larger number, it reached 1 in fewer steps than 6. This conjecture has been tested for an incredible number of numbers, up to more than 2ˆ60 = 1.152.921.504.606.846.976 cases, without finding any counterexample. However, it still remains a mystery whether there is a number that does not satisfy the conjecture.

Graphical representations of the Collatz conjecture

The directed graph of orbits is a visual representation that facilitates the understanding of the behavior of numbers under the rules of the Collatz conjecture. In this graph, each number is represented as a node, and the connections between them show the steps followed by the conjecture process. When following the sequence of a number, the nodes are connected by arrows that indicate how the number is transformed at each step. Although even numbers are generally omitted from the representation for simplicity, the graph illustrates how the numbers “orbit” around certain cycles, such as 1 →4 →2 →1.

In the image above, we can see an example of the directed graph of orbits, where we have highlighted in black the numbers 3 and 21. The number 3 refers to the sequence of 6, since in this graph the even numbers are omitted to simplify the visualization.

We note that 21 quickly reaches 1, since it only passes through even numbers on its way, as we saw in the previous example. On the other hand, the number 6 first becomes 3, then pass through the number 5, which will finally take it to 1 after several passes through even numbers. 

It is also interesting to note that the number 9, although relatively small, follows a longer sequence: it goes through the numbers 7, 11, 17, 17, 13 and 5, and finally reaches 1, after a total of 19 steps. 

Below is a graph in which the X-axis shows the different initial integer values, while the Y-axis represents the number of iterations required for each number to reach the value 1.

In summary, the Collatz conjecture is an apparently simple problem that, to this day, still has no formal proof. Although it may seem a statement of little relevance or practical utility, this conjecture has applications in various fields, such as number theory, cryptography, algorithm analysis and artificial intelligence. In these fields, the study of complex sequences and their behavior under specific rules can offer valuable insights for solving larger problems and understanding mathematical patterns.

Have you been fascinated by the simplicity and mystery of the Collatz conjecture? Now it’s your turn: take the number 27 and start the sequence. How many steps will you need to get to 1?

If this challenge got you, don’t keep it to yourself! Share it with others who are curious about mathematical riddles and find out together who can solve the challenge the fastest.

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Overcoming Math anxiety

Girl studying at home Homeschool

 

How many times have we heard people say ‘I am not a numbers person’ or ‘Math gives me the jitters’? Many times, it would seem. Math anxiety is, at the very basic level, a fear of using numbers in any form, be it calculating or understanding concepts through numbers and data, large or small. 

The Mathematical Association of America has said that according to some estimates, 93% of American adults experience some form of Math anxiety. Math anxiety has been studied by psychologists and scientists for years, the first such identification of ‘number anxiety’ going way back to 1957. 

An initial understanding of Math anxiety tried to separate it from general anxiety and performance. If we are confident in Math, we perform better at it. The Program for International Student Assessment conducted a massive global study of 15-year-old students across 64 countries in 2012. The study found that Math anxiety was negatively related to Math performance. Students with high levels of Math anxiety performed poorly in the subject compared to those who displayed lower levels of anxiety. The Math anxiety lights up a fear centre in the brain, and it shuts down the problem-solving ability of the student, even though he/she is very capable. 

Math anxiety’s negative impact 

Math anxiety is very real, and could prevent a student from reaching his/her optimum career potential. The lack of confidence in Math, and the early years of negative beliefs about one’s innate ability with numbers is known to lead to a persistent anxiety that is prevalent throughout one’s student years and even later. As a result, many students hesitate to choose STEM, instead opting for subjects that do not involve Math. Even though they may have a great ability to grasp complicated concepts, and the intellect to solve problems, students evade STEM subjects so as not to deal with numbers on a daily basis. 

Gender inequality

Several studies show that math anxiety seems to be higher in females than in males, although gender-related differences regarding math performance are small or non-existent. This illustrates that math anxiety has a gender bias due to the impact of gender stereotypes. These stereotypes generate subconscious self-barriers among girls, who regard themselves as less capable of performing well in math and STEM.

Math at work

As the future of work demands more use of Big Data, analytics and quantifying human experiences, the need for talent in numbers is only set to increase. The US Bureau of Labor Statistics has estimated that between 2016 and 2026, there will be a 28% increase in occupations that use math heavily. This means that students who are comfortable with Math can lean into these professions and have better job prospects. But what about those dealing with Math anxiety? It will be a choice of facing the anxiety and overcoming it, or finding other occupations that do not need Math. 

Overcoming Math anxiety

The love (or the hate) for Math has seeds sown in childhood. Parents and teachers have a crucial role to play in making math fun for children. They can do this by ensuring that their own anxiety, if any, is not transferred to the child. 

It is also important to break stereotypes and imaginaries concerning math: We need to overturn the perception that maths is a difficult, boring and men-concerning subject.
Parents can be conscious of introducing Math concepts of problem-solving in everyday life situations. Math should be positioned as a fun subject through games, puzzles and fun activities that take the fear out of using numbers and calculation. Also, schools and institutions must perform a task to draw attention to women role models in STEM. 

Technology can help make Math fun in the larger context of game-playing, problem-solving and fun-based learning activities. Apps and websites with an interactive experience can appeal to students’ achievement goals, therefore reducing the fear of numbers. 

Dealing with Math anxiety demands a holistic societal approach with increased awareness at all points of interaction in a student’s upbringing – home, school, education system and peer group. The good news is that Math anxiety is increasingly being recognised as a psychological problem. The solutions are forthcoming, too, if we are willing to pay attention. 

Sources:

  • npr.org: Math anxiety is real. Here’s how to help your child avoid it.
  • girlsschool.org: The math-anxiety performance link. A global phenomenon.
  • Frontiers in psychology: Gender differences regarding the impact of math anxiety on arithmetic performance in second and fourth graders
  • Harvard business Review: Americans need to get over their fear of math.

 

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5 reasons to switch to online software

Scientific studies

In the last few years, digital tools are gaining popularity. As in many other aspects of life, digitalization is finding its place in the laboratory environment. It is not a surprise. The list of advantages that the switch to online software has in day-to-day work is long.

On the other hand, the jump from paper to digital can be a bit overwhelming at times. To help you in your decision, here is a list of 5 reasons why you should consider making the move, if you haven’t done it yet. 

1. FLEXIBILITY: 

Coronavirus showed us how important it is to be able to access your data and your work when you are far away from your laboratory or workplace. Now that we are leaving the pandemic behind, there’s still plenty of situations where we need to work remotely: when you work from home as a way to improve work-life balance (specially important to solve gender gap 1, 2); when you are abroad for a conference or visiting another lab; or even when you move forward in your career and start a new position. In all these cases, the flexibility of online software can be a great advantage: You can access it anytime, anywhere and from any device. The possibilities are virtually endless. 

2. REPRODUCIBILITY: 

One of the biggest concerns in science is reproducibility. According to a Nature’s survey3 of 1,576 researchers, 52% of them think that there is a significant “crisis” of reproducibility. Under the same line, an online poll of members of the American Society for Cell Biologist4, more than 70% of those surveyed afirm to have tried and failed to reproduce an external experiment, and even more surprisingly, 50% of them have failed to reproduce their own experiments. 

The reasons behind this are many: from poor analysis or experimental design, to human error or lack of complete methods’ information. The list goes on, but in many of these cases, using online software could help increase reproducibility. They are designed to be consistent, follow industry standards and facilitate automated experiments and data collection.   

3. SHAREABLE:

Online tools are also designed to share your files and results easily with colleagues and collaborators. Aside from facilitating record-keeping and making your life easier, sharing is more important than ever. In the past years more publishers and funders are encouraging, even demanding, depositing raw datas and protocols in a repository. In this scenario, using online tools can become a huge advantage. 

Also, improving the way you share your raw data, results and protocols positively impacts the reproducibility of your experiments. A study published in Plos One5 indicates that sharing detailed research data is associated with increased citation rate. Sharing not only improves your work but also the quality and robustness of science in general. 

5 reasons to switch to online software: flexibility, reproducibility, shareable, save time, increase productivity.

4. SAVE TIME: 

Online tools help you to simplify your workflow and save time. Although in many cases you can do the same work with pen and paper, the online versions make it quicker. They are designed to free you from normally boring and time-consuming tasks and to improve one, or several, key steps of an experiment (creation, execution, data collection, data processing and calculations). 

Moreover, using a toll helps to compare results across multiple runs and, even more exciting, when you deal with large amounts of data and samples, it can help you see the results in a global way and find connections. 

5. INCREASE PRODUCTIVITY: 

And last but not least, using online tools improves productivity and efficiency. Besides saving time, using online software avoids the mistakes and typical human errors that can ruin an experiment: misscopy data, transcription errors, data loss, haphazard record storage… They also help to optimize workflow and automate processes. In summary, using online tools is a great way to  boost your productivity in the lab.

As you can see, everyone can benefit from changing to online software. From small labs to big biotech companies. There are plenty of options out there. If you are thinking of making the transition, we recommend to start small first and try different solutions to find the one that suits you and improves your workflow. 

At Bufferfish, we do our best to create chemistry software and result analysis tools to make your life easier so you can really focus on your research. 

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Celebrating the uniqueness in every student

Team work women

Bridging the gap between classrooms and real world 

The formulaic, rote learning approaches to classroom education are increasingly outdated in a fast-changing, technology-driven world. As technology advances at a fast clip with every passing year, the most rewarding careers are those in which the professionals can use innovative and creative approaches to what they studied from textbooks. 

Take math and science, for example. We live in a complex world where our every habit and behaviour have the potential to be quantified. We want to know how many hours we sleep, how many steps we walk every day, how our heart beats while grocery shopping, and how our body is responding to a type of music. This is the era of Big Data, analytics, pattern recognition and artificial intelligence. Classroom education can be most effective if teachers make meaningful connections between the academic lessons and the real world. 

Personalized pathways for learning

If education can be flexible enough to make room for every student’s strengths and learning inclinations, it is more than half the battle won. If students are equipped with the power to design their education and choose what to learn and how to learn (through informed decision making), they are likely to be more invested in making the most out of their classroom hours and beyond. 

Every student is unique. The education system must be flexible to celebrate this uniqueness and help students achieve their career goals. This is already being done in some places. For instance, Leiden University in The Netherlands offers flexible learning pathways in which students can take charge of their education to align with their personal ambitions. They will be guided by the teachers in creating a unique education pathway that complements their talents and interests.

One student may be naturally inclined towards numbers while another may be good at understanding concepts. One student may be quick at spotting errors while another may be good at words and writing. Teaching can be most effective if each student’s strengths are optimized to create a wholesome learning experience. 

Universities started offering flexible learning pathways.

A plan for the future 

Personalized learning pathways have benefits that go beyond the classroom learning experience. Take the example of Rhiannon Dunn, a ninth-grade teacher at Science Hill High School in Johnson City, Tennessee, USA, who has applied the concept of personalized learning that students can choose for themselves. Dunn started a literary circle in which students have the freedom to choose any book for their independent reading time. They also get to decide how the teacher assesses them on this learning activity. It gives a strong message to students that they have a voice in their learning journey. 

The student takes an active interest in charting a course of action for the future by linking education to the career that they most likely see themselves in. They take into account their interests, natural strengths and curiosity while aligning them with the profession of their choosing. Students are able to draft a plan for their professional life, and be proactive in the decision making as they pursue their education. 

Since students take ownership of their education, they are likely to be more interested and invested in the learning process. They become active learners from passive observers in the classroom. When a personalized learning pathway for a student includes creative teaching methods, students will ideally continue learning beyond the classroom, too. 

What happens if a student changes her/his mind after a while on the pathway? This could happen as students cannot be expected to know for sure what they want. The education pathway should be flexible enough to allow a student to explore additions or changes without feeling like she/he is at a loss or has to completely start over. Education counselling is, therefore, extremely important to ensure that the student is making a commitment, and is allowed some elbow room to tweak the learning pathway.   

Instilling the spirit of curiosity 

A creative approach to learning has to start in the classroom, where students gain the confidence that learning need not to be fixed or given. It is, rather, a lifelong process that can be playful and encourages the student’s spirit of inquiry. Curiosity and the desire to know is at the heart of meaningful education. This curiosity is then given wings by personalizing learning so that the student can move forward at her own pace and time, using the format that gives the best results. 

A unique path for every student 

We live in a world that is increasingly celebrating our uniqueness, and offering personalized solutions to our needs. Be it advertising, technology, health, beauty or fitness, personalization has seeped into every part of our lives. Why should education be any different? 

Charting out a unique pathway for every student is an exciting prospect in which the student, the main stakeholder of education, has the maximum say and also the maximum benefit from the process. 

Other Sources: 

 

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Two years of distance education: is the revolution here to stay?

e-learning school online

The pandemic has forced schools to adapt to online training

The COVID-19 pandemic has led to an unprecedented revolution in education. Confinement forced classes to be adapted to online formats, a huge challenge for many professionals and educational centres. 

After nearly two years since the COVID-19 outbreak, it’s time to look back and analyse how the educational community has experienced the impact of the pandemic and the online transformation. And we ask ourselves: Is online education here to stay?

The role of technology

The use of technology in the classroom was already a tendency and a major concern in educational centres before the pandemic: In the United States 85% of district administrators reported that using digital learning resources was a high priority in 2019, and already in the 2017-2018 academic year, 21% of public schools offered at least 1 online course. The pandemic forced to speed up this tendency, with 80% of households with children learning online in Spring 2020.

Technology has allowed education to continue while the schools were closed, showing that it can provide a plan B in times of shock. The use of platforms that facilitate videoconferences, chats and tools to share documents provided a channel to deliver remote learning and keep students and teachers in contact. 

On the other side, specialized programs and applications to work on specific content helped students in a situation where they had to work completely on their own. These tools have definitively entered the classroom and will undoubtedly mark the education of the future.

MathType is a clear example of this situation: The use of the equation editor experienced a huge growth (more than 400%) during the strong lockdown months. Since then, the number of users that open documents with formulas hasn’t stopped growing, showing that the digital content that was generated during the pandemic will continue to be used.

Confinement forced classes to be adapted to online formats.

Hybrid learning

During the COVID-19 pandemic, nearly 90% of European higher education institutions adapted their learning formats to online or blended models. But even now that the situation of the pandemic allows us to get back to face-to-face lessons, online training continues to be an option that can be combined with in-person attendance. This is called hybrid learning, and takes the best of each model, from closeness and face-to-face contact, to the advantages provided by educational equipment, tools and applications.

Hybrid learning has a lot of potential to be explored. For instance, it could help ill students to continue with their courses in a normal way. It could also be a solution for schools in some rural areas, where people have a long journey to school, everyday. Thanks to technology, hybrid learning is an interesting model for education, as it allows an easy adaptation to the needs of each centre, type of student, and training.

Challenges of online education

However, the online or hybrid models also pose great challenges for schools and education professionals, as well as for students and their families.

To begin with, not all homes have the necessary digital tools and a stable internet connection. 

This creates a digital divide that results in difficulties in accessing education. Moreover, these difficulties strike vulnerable educational communities harder. According to UNICEF, 3 out of 4 students who cannot be reached by the remote learning policies come from rural areas or belong to the poorest households. 

The conditions in which the students work at home are also a drawback of online education.  A third of the high education students in the EU do not often have a quiet place to study, and almost 60 % reported they do not always have a reliable internet connection. The experience of the pandemic suggests that, even in developed countries, there’s still a long way to go until the implementation of remote learning does not leave anyone behind. 

Additionally, new skills are required to master technologies. Education professionals must adapt to these new digital tools, while students must be able to acquire the skills that promote their independence, flexibility and willingness to learn and improve beyond the school years.

Adapting the contents

Another challenge is knowing how to efficiently adapt content to an online format. Giving classes by videoconference or hanging the subjects in a cloud may not be sufficient if we expect the same level of results. A significant proportion of students in the EU (47.43 %) consider that their academic performance was negatively affected when on-site classes were cancelled, a clear sign that technology didn’t completely succeed in substituting face-to-face education. 

In the digital model, contents must be adapted through applications and programs that make the subject matter more attractive and understandable. This is especially challenging in STEM subjects, where the materials (graphics, equations, lab work, etc) are more difficult to adapt to a cloud format. 

An example of a successful adaptation of traditional material to a digital format is the recent WirisQuizzes graph features, that were built during the pandemic and are now a digital support for the most visual parts of mathematics: geometry, functions and statistics.

While challenges in online learning exist, educational tools and models will evolve to overcome them. There is still a long way to go, but most would agree that the online learning revolution is indeed here to stay. The next question is: Where do we want it to take us?

 

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Making people’s STEM work more meaningful