AI Researcher

The 21st century has seen a recent boom in AI-related products and discoveries. From new transformer-centered model architectures to Dall-E to ChatGPT, new innovations are now rapidly expanding the horizon of what is possible for artificial intelligence and its applications. Recently, natural language processing (commonly referred to as NLP) has been in the forefront of this so-called “AI revolution,” and for good reason too. NLP products and services (ChatGPT and other generative AI chatbots, for instance) have brought to many people’s attention the practical, everyday uses AI can have. Moreover, creations centered around NLP have fundamentally altered — and will more likely than not continue to alter — many fields, particularly the field of education.

Although almost every educational subject would benefit a great amount from these innovations in NLP, this article will focus on applications in world language education. This is because NLP and current generative AI technologies pair very well with themes present in foreign language learning. The process of learning a language strikes a good balance between black-and-white, almost “binary” logic and fluid writing which offers more leeway: firstly, a main aspect of picking up a new language is applying logical rules (such as grammatical laws) that have a relatively well-defined set of correct and incorrect answers. Indeed, this aspect is similar to qualities present in math, science, and other STEM subjects. That said, the language classroom rarely explores the nitty gritty of logical relations present within these fields, ones that can be quite complex and may result in glaring issues for an AI model not trained to solve a specific problem. Language learning offers leeway in this sense because within the context of fluid writing, logical errors (which are bound to happen for any complex and nuanced subject) would be less detrimental.

Though AI technology has definitely impacted language learning, technologies like Quizlet or Duolingo have made large ripples in the field prior to any mass-scale wave of AI innovation. So, then, what does the future look like?

Michael Cai

What developments in AI mean for Language Education

Ever since the release of show-stopping innovations like Open AI’s new generative AI chatbot, ChatGPT, or the company’s original artwork generator, Dall-E, artificial intelligence has been on everybody’s minds. Machine learning is still a relatively young and emerging field, and most of these mainstream technologies are all fairly new, so it’s no surprise that people have begun to gravitate towards this AI trend — after all, it shows a lot of potential. As a result, from cooking to writing essays, there have been countless AI-related topics online resources have covered, each one offering ways to use AI to its maximum potential. A vast majority of these resources concern AI prompting, the act of engineering queries to feed into AI chatbots like ChatGPT.

Now, prompting can be used in an infinite number of ways. This article covers a small pool of those methods, specifically how the act can be incorporated into language learning. Language learning is a field that AI is bound to greatly impact. In fact, apps like Duolingo have already incorporated some AI-based elements. AI and languages indeed go hand-in-hand. This is because the bulk of language learning stems from memorizing and being extremely comfortable with a set of well-defined rules. Programs like AI are quite good at identifying patterns — and in turn, rules — so they naturally excel at language learning and language translation (in fact, the field of natural language processing — teaching computers how to understand natural human languages — now mainly concerns machine learning). With this in mind, here are some of the best prompting tools to use when navigating the potentially daunting task of learning a new language from scratch.

This first section encapsulates the tools that are used in more niche scenarios; they may be powerful, but not necessarily common. When it comes to a ranking structure, these would comprise the lower five tools.

Top 10 Prompts for Learning Languages

In the fast-paced world of education, time is a precious commodity for STEM teachers. The administrative duties that accompany their core teaching responsibilities can often be time-consuming and tedious, taking away valuable moments that could be better spent engaging with students and refining their instructional techniques. Fortunately, Artificial Intelligence (AI) presents a transformative solution to streamline administrative tasks, enabling educators to reclaim their time and focus on what truly matters - fostering a stimulating and nurturing learning environment for their students. This article delves into how STEM teachers can leverage AI to make their administrative duties more efficient, covering tasks such as writing emails to administrators, crafting syllabuses, and handling other miscellaneous non-teaching responsibilities.

Automated Email Composition to Administrators:

Writing numerous emails to administrators for various purposes, such as requesting resources, addressing student concerns, or seeking approval for educational activities, can be time-consuming for teachers. AI-powered email composition tools can significantly expedite this process. By analyzing past email interactions and using natural language processing, AI can generate draft emails that align with the teacher's communication style and the specific context of the message. For example, when requesting additional laboratory equipment, the AI system can draft a detailed email outlining the requirements and potential benefits to students, saving time and effort for the teacher. This 

 on lowtech.ai can help teachers with this task!

Umar Farman Samdani

Revolutionizing Administrative Efficiency in STEM Education

There’s a common perception that mastering a foreign language means being able to conjugate and decline words or being able to string together complex sentences in split seconds. There is truth to this; world language classes often adopt this heuristic of measurement, and foreign language proficiency tests frequently examine students’ ability to perform in these respects. The only issue is that when it comes to practical applications of a language, understanding and utilizing its grammatical rules only contributes a fraction of what’s necessary to be “fully proficient.” When it comes to interacting with a native foreign-language-speaking society, knowledge of culture can also be key.

As mentioned before, standard world language curriculums do not emphasize learning cultures associated with languages. Yet understanding cultural taboos, traditions, or dialectal variations equips students with the tools to formulate contextually appropriate sentences and form stronger connections in the process. So then why is culture often forfeited in the classroom? One of the main answers is a lack of resources and time. Languages are hard to learn — they require students to memorize large masses of vocabulary, sentence structures, and grammatical exceptions. And considering the limited amount of time each teacher has in a day to teach and concoct lesson plans, it is understandable that less emphasis is placed on cultural learning.

However, with recent developments in artificial intelligence, there is a solution. Generative AI chatbots in the form of tools like ChatGPT are practically catered towards this issue. These machine learning models are trained on vast amounts of data on the internet, making them highly educated on almost any topic thinkable. As a result, these kinds of large AI chatbots are customizable to a wide range of tasks, especially when it pertains to subjects well-defined online such as cultures of different societies. The streamlined prompt-output structure of these tools (i.e, users feed in a prompt (or input) and the chatbot spits out a response (or output)) are particularly useful for saving time, the main issue faced in this scenario.

AI As a Gateway to Cultural Learning in the Classroom

In the ever-evolving landscape of education, the integration of Artificial Intelligence (AI) into teaching methodologies has shown immense potential in transforming the way students approach difficult math and science problems. STEM (Science, Technology, Engineering, and Mathematics) teachers can harness the power of AI to offer detailed explanations, propose new spin-off or follow-up questions, and provide alternate ways to solve problems, creating a more personalized and engaging learning experience. Let us explore some examples of how AI can be employed to tackle complex mathematical and scientific challenges and enhance the learning journey for students.

 Imagine a challenging calculus problem that involves finding the limit of a complex function as it approaches infinity. The AI-powered teaching tool can break down the problem step-by-step, providing detailed explanations at each stage of the solution. It can elucidate the fundamental concepts of limits and continuity, guiding the student through the process of simplification and highlighting the significance of each algebraic manipulation. By providing instant feedback and ensuring a thorough understanding of the concepts, the AI system encourages students to explore further and strengthens their problem-solving skills. Consider, for example, this 

 I generated on LowTech.ai. The prompt asks for a STEM question and a reference age for the explanation. Let’s see the code in action:

Two cyclists start 30 miles apart, and begin cycling towards each other at 15 mph. The instant they begin, a fly goes from one cyclist to the other, then back to the first cyclist, and so on, always flying between the cyclists. The fly flies at a constant 30 mph. How far in total does the fly travel when the cyclists meet?

Using AI to Explain Tricky STEM Problems to Students

Writing letters of recommendation is an integral part of a teacher's role in supporting their students' academic and professional journeys. These letters provide valuable insights into a student's abilities, achievements, and potential, assisting admissions officers and employers in making informed decisions. However, crafting personalized and impactful letters for multiple students can be a time-consuming and challenging task. In this era of rapid technological advancements, artificial intelligence (AI) can lend a helping hand to STEM (Science, Technology, Engineering, and Mathematics) teachers, enhancing their ability to write effective and tailored letters of recommendation.

Natural Language Processing (NLP) is a branch of AI that focuses on the interaction between computers and human language. NLP techniques can empower STEM teachers by providing assistance in various aspects of letter writing, including structure, content, and grammar. For instance, AI-powered tools can analyze the language and tone of a teacher's existing letters to identify patterns and suggest improvements. These tools can also help ensure consistency across multiple letters while maintaining the unique voice and perspective of the teacher.

Using AI to Write Letters of Reccomendation

In the ever-evolving landscape of education, effective communication plays a pivotal role in fostering a dynamic learning environment. For STEM teachers, the ability to engage and connect with students, parents, and school administrators is paramount. With its versatile capabilities and intuitive interface, Chat GPT has the potential to streamline communication processes, provide templates for reminders and start-of-semester communications, and facilitate efficient interactions with parents and school administrators. This article will explore some of these applications and provide specific examples for reference.

Engaging and connecting with students is crucial for effective teaching. Chat GPT can assist STEM teachers in various ways to facilitate better communication within the classroom. Teachers can use Chat GPT to spark interactive discussions and debates by generating thought-provoking questions or prompts related to the lesson topic. This encourages students to actively participate, share their thoughts, and learn from their peers. Teachers can also use Chat GPT to draft emails that fulfill this same purpose – sparking thoughtful discussion in a virtual space.

How STEM Teachers can Use AI to Facilitate Communication

It’s no secret that artificial intelligence is booming. Within less than a year, Generative Pre-training Transformers (GPT) have evolved from a research subject relatively unknown by the wider public to household names in communities all over the world. This might partially be due to the fact that the capabilities of artificial intelligence and machine learning have increased exponentially since the advent of a new AI model called the transformer, and more so in 2017, when researchers introduced the notion of capturing relationships between words in an input sentence (known as “self-attention”). However, one potentially greater reason for AI’s popularity is that with the focus on natural language processing, AI tools have become extremely useful to almost anyone — not just researchers.

ChatGPT and other generative AI-powered chatbots are the harbingers of this “natural language processing revolution.” Their ability to parse and comprehend input text at such an efficient pace lends itself to almost every field and every corner of daily life. One application in particular is the use of generative AI in the classroom, specifically language classrooms. The main purpose of world language classes is to promote the ability to parse through texts of different languages, so it’s only natural that generative AI could help. At the same time, there are a multitude of other ways in which AI can aid in communication — some which are unique to language classrooms and others which can apply to any educational or interpersonal setting.

Helping communicate topics of study to students is one of the more general usages of AI. In fact, for any subject that includes complex concepts, communication aid can be vital on the part of the teacher. One good way of conveying these ideas is through analogies, since they can offer a visualization for something that’s otherwise hard to grapple with. Since generative AI gathers and learns from basically all the information on the internet, it has the capability to be highly customizable to the user’s needs, and as such, can act as an analogy generator. In fact, an example analogy generation prompt can be found 

 (note that if you use the prompt for foreign language concepts, you will need to specify the language in the “concept” field).  Additionally, an example input and output can be seen below. This example was taken from ChatGPT since as of the time of this article, it is the leading generative AI tool. The prompt on Lowtech AI is easily migratable to ChatGPT (just click “Show Prompt” and replace the placeholder words in double curly brackets).

AI-based Communication Help in the Language Classroom

The recent explosion in AI-related products has permeated almost every field. Although areas such as biomedical research and engineering were the first ones to be impacted on a large scale, recent developments in machine learning have made the field relevant in everyday lives. Specifically, the creation and proliferation of generative AI resulted in tools such as chatbots. Examples like ChatGPT and other household AI tools have already found their way into the classroom of many schools. But more often than not, it has been interpreted as a negative force. After all, instructors frequently see AI as a powerful yet hard-to-be-traced device students can use to cheat.

That said, AI has much more potential than just a way to cheat. Ironically enough, it can serve as a major source of guidance for instructors. When it comes to researching, designing, and learning of materials for teaching, generative AI can actually be quite a useful tool. This article focuses on how AI can positively impact language teachers in particular, though it can be extended to other subjects. Language learning is unique in that it incorporates elements from both STEM (science, technology, engineering, and math) classes as well as humanities classes like English and history. Specifically, language classes can be known for possessing complex ideas and grammars that can take up an almost mathematical appearance. At the same time, the notion of writing essays and interacting with other people and societies is analogous to work done in the humanities and arts. It can be difficult to balance these two elements, and paired with the momentous amount of material language teachers are tasked with teaching, world language classrooms can often be the hardest ones to get right. As a result, they’re the ones most benefited by AI.

The main reason why AI can be such an annoyance when it comes to cheating is actually the same reason why it can be so effective when researching the best ways to conduct a desirable classroom environment. Generative AI chatbots are customizable and create unique responses. That means these AI tools can respond to almost any question with a helpful response, and that the response given will not be a piece of text found somewhere on the internet, but rather one uniquely generated by the machine learning model. One feature these AI chatbots are especially proficient in is outputting customized summaries (i.e., summaries of a topic that follow a certain set of conditions and restrictions). This is because generative AI models learn from a large dataset that consists of text from the entire internet, which allows the AI model to be aware of almost everything on the internet at the time it was trained. The caveat of this is that any model will always be a little behind on news and contemporary information. The AI learning process (known as training) often takes a long time for large models like OpenAI’s ChatGPT, so no matter what, there will always be a delay between what’s currently available on the internet and what generative AI models know (for reference, ChatGPT 3 is only aware of information up to 2022).

A case study on how AI can help language teachers

AI in the Classroom

In the rapidly evolving landscape of education, teachers are constantly seeking innovative ways to engage students and enhance their understanding of STEM subjects. With the advent of advanced language models like ChatGPT, educators now have a powerful tool at their disposal for brainstorming new instruction ideas and conducting in-depth research. This article explores how STEM teachers can leverage ChatGPT to foster creativity, explore new perspectives, and deepen their understanding of various topics, ultimately improving their instructional practices.

ChatGPT can serve as a valuable brainstorming companion for STEM teachers. By engaging in a conversation with the model, educators can generate a wide range of ideas for lesson plans, projects, and activities. This article will offer some practical AI prompts for teachers to experiment with, as well as further explain the advantages of ChatGPT integration in the classroom.

How AI Can be Used to Develop Innovative Teaching Methods

Grading tests can be a time-consuming task for educators, often taking away valuable instructional time. However, advancements in artificial intelligence have introduced new possibilities for streamlining the grading process. In this article, we will explore how STEM teachers can utilize Chat GPT to grade tests efficiently, saving time while providing valuable feedback to students.

Generally, there are many ways to implement Chat GPT into grading procedures. The primary step, however, should be to collect a substantial amount of test responses that cover a wide range of correct and incorrect answers. This data should be representative of the skills and knowledge being assessed. Next, the AI model needs to be trained with the collected data, with prompts highlighting exemplary answers versus those that lack fundamental understanding. After training the model, teachers can input sample student responses and tweak their prompts to obtain a desired result.

How AI Data Analysis can Help STEM Teachers with Grading

It’s inevitable to make mistakes when learning a language. After all, every language is rife with intricate linguistic subtleties and nuances only understandable after years of exposure. As valuable as mistakes can be, they’re practically useless if left ignored or undetected. While instructors and native speakers can definitely be sources for identifying mistakes, oftentimes students might not have these resources at their disposal. That’s where artificial intelligence comes in.

AI text analysis isn’t anything new; tools like Grammarly and spell-check have existed since the late 20th century. However, most of these tools are either hidden behind a paywall or limited in what they’re able to do. Each tool dedicated to a certain task, whether it be checking for grammar or spelling, is restricted to a particular set of capabilities. Additionally, many of these tools only work on the English language, a fact which immediately invalidates a large bulk of existing spelling and grammar checkers when it comes to learning a new language. Recently, however, a more versatile form of AI has emerged in the form of ChatGPT, Google’s Bart, and other generative AI chatbots. These tools are unique in that they aren’t programmed to complete one specific task, but rather, they are given a large dataset consisting of information from all over the internet to learn from, so as to be able to “generate” responses to any question asked (hence their name). Not surprisingly, text analysis is a big feature of generative AI tools. And while specific tools targeted for grammar help might be confined to a small repertoire of capabilities, these models can be customized to help with whatever question, no matter how random or obscure.

Let’s take a look at what generative AI can actually do.

AI Text Analysis for Language-Learning

Many STEM teachers face a particularly challenging pedagogical task: distilling large amounts of complex information into a digestible format. While the course textbook serves as an excellent source of information and practice problems, students often prefer condensed study guides, note packets, or cheat sheets. However, creating such materials requires substantial effort and time. Teachers may prefer utilizing this time for in-class presentations – which, unlike summarization, is a task that requires more human tailoring and input.

With Chat GPT, teachers can expedite the creation of study guides and other “one page” note sheets for their students. This article will provide examples of how AI can accomplish this task, and offer suggestions for teachers interested in exploring this topic further.

Understanding General Topics with Summary Sheets

Even without a textbook as a reference, ChatGPT can create one-page summary sheets for a specific STEM topic. Consider a 

. All the prompt requires is an academic topic. Then, the AI generates a summary sheet consisting of essential definitions, main ideas, and basic examples. An educator can then utilize this cheat sheet directly, or change the prompt slightly to cater to their needs. For example, the educator can ask the AI to order the example questions in increasing difficulty, or reorder and replace certain sections.

AI Summarization and its Benefits to STEM Teaching Methods

When it comes to learning about different parts of the world, one of the largest hurdles is gaining familiarity with different languages. Compared to math, history, and other subjects, mastering new languages can be particularly frustrating due to its reliance on the learner’s individual proactiveness. Most likely, even after carefully paying attention in an introductory course, there might still be a handful of beginner sentences that seem almost incomprehensible due to their use of unfamiliar vocabulary or obscure grammatical structures. It’s often up to the learner to go beyond the standard curriculum in order to truly pick up the language, a task which may seem daunting when done alone.

Fortunately, with the advent of generative AI tools like ChatGPT or Google’s Bard, there are many new tools available to help with this task — particularly AI summarization. Now more than ever, generative AI tools are utilizing what is called a “transformer” architecture. This state-of-the-art AI model enables tools like ChatGPT to understand relationships between words as well as to remember and utilize information from all over the piece of text. These traits, which previous iterations have struggled with, allow the AI to be highly adept at summarizing large bodies of text.

Teachers