Google supports The Last Mile Education Fund $300k to increase persistence in technical pathways for low-income, underrepresented computing students.
Three Google Career Certificate graduates share their tips for completing a certificate, finding your dream job and boosting your career.
Google’s exploreCSR Program is helping Kean University students Eric Ponte and Xavier Amparo change the face of pill detection.
Google celebrates Computer Science Education Week with free learning resources and support for local organizations closing equity gaps in CS.
Google for Education collaborated with research partner Canvas8 and advisor and consultant American Institutes for Research to conduct a global study in 24 countries on …
Maria Running Fisher Jones first learned about balancing checking accounts and filing taxes at age 7 — thanks to her primary school teacher. Though finance didn’t end up being her calling in life, education has been a consistent theme throughout her career. She first studied education, even earning her master’s degree, but ended up finding a home in law.
Now as senior corporate counsel in Google Cloud, Maria also takes time to partner with Googlers and people in her community to raise awareness of issues that are impacting Indigenous communities in the United States, like the one she grew up in, and expand opportunities for Indigenous-owned businesses. I chatted with Maria over Google Meet to hear her story and learn about how education has always been a cornerstone in her life.
Can you tell us a bit about yourself?
I was raised by a single mother on the Blackfeet Indian Reservation in Northwestern Montana, a community struggling with a 69% unemployment rate. The estimated poverty rate of Native Americans living on reservations is nearly double the national average and the highest in the country.
My family saw education as a way to lift ourselves and our community — a way to learn and gain access to connections to give back. My mother ingrained the value of education in me deeply: I vividly remember a time when she wouldn’t allow me to participate in a basketball game because my grades had slipped. Even worse, my mother made me tell my coach and teammates the reason I was to miss the game. It’s those life lessons that have brought me to where I am today.
The more I learned about the tech industry, the more I discovered how much it could be used for good.
How did you get into law?
I didn’t initially anticipate practicing law as a career. Entering college, I was set on a degree in education with a plan to teach high-school English, thanks to the influence of my primary school teachers.
While studying for my master’s in education, I became particularly interested in educational disparities, like why are some children afforded a better education and more resources than others? I began researching laws to educate myself and started to realize that a law degree could help me affect positive change. In some sense, I really fell into a law degree by virtue of following my passions and natural curiosity.
What shaped your interest in tech?
Technology, its importance and impact in the world, wasn’t something I spent much time thinking about while in Montana. Instead of video conferences and emails, I was picking up the phone to connect through a landline or showing up to have a cup of coffee.
But the more I learned about the tech industry, the more I discovered how much it could be used for good. I saw how this was the future and how it could connect my family and community to opportunities in a more equitable way. It’s why I participated in a Wi-Fi connectivity project with GAIN, Google’s Aboriginal and Indigenous Employee Resource Group. It’s how I found the ability to connect my education degrees to tech law. At Google, I’ve been able to do both.
How do you connect your work at Google to the causes you care about?
Giving back and engaging in community is critical in my life. Leaving the Blackfeet Indian Reservation in Montana is still something that pains me to this day. Leaving family has always been a challenge for me, but sharing my culture and raising awareness on issues facing Indigenous people has filled the void of missing home. Since joining Google, I’ve had the opportunity to provide awareness through various channels, including a Talks at Google interview with activist Kimberly Loring HeavyRunner and a Careers on Air virtual event celebrating Google’s Aboriginal and Indigenous communities.
Native Forward, the U.S.’s largest scholarship program for Native students with more than 16,000 recipients from over 500 Tribes, provided the funding to support my law school education. Recently, I was part of a group of Googlers who reviewed its scholarship applications, and I donate monthly via our internal platform that allows for company matching.
In addition to the work I do at Google, I also started a company, TPMOCS, in 2014, specializing in handcrafting children’s moccasins. We employ Native American artisans in rural communities and give a portion of profits to organizations on reservations supporting children in need.
Is there anything else you’d like to share?
During a trip back home to the Blackfeet Indian Reservation, I spent time with family and elders, and had a traditional naming ceremony for my children. I also had time to reflect on my life choices. Some, if given the chance, I would do over, but one that I’ve never second guessed is joining Google. As I speak at events, I’d like Indigeous youth and young professionals to know that you too can pursue a career in tech and still remain true to yourself. Representation matters and working at Google provides me with a platform to highlight interests and issues close to my heart. Google welcomes our voices.
Maria Running Fisher Jones first learned about balancing checking accounts and filing taxes at age 7 — thanks to her primary school teacher. Though finance didn’t end up being her calling in life, education has been a consistent theme throughout her career. She first studied education, even earning her master’s degree, but ended up finding a home in law.
Now as senior corporate counsel in Google Cloud, Maria also takes time to partner with Googlers and people in her community to raise awareness of issues that are impacting Indigenous communities in the United States, like the one she grew up in, and expand opportunities for Indigenous-owned businesses. I chatted with Maria over Google Meet to hear her story and learn about how education has always been a cornerstone in her life.
Can you tell us a bit about yourself?
I was raised by a single mother on the Blackfeet Indian Reservation in Northwestern Montana, a community struggling with a 69% unemployment rate. The estimated poverty rate of Native Americans living on reservations is nearly double the national average and the highest in the country.
My family saw education as a way to lift ourselves and our community — a way to learn and gain access to connections to give back. My mother ingrained the value of education in me deeply: I vividly remember a time when she wouldn’t allow me to participate in a basketball game because my grades had slipped. Even worse, my mother made me tell my coach and teammates the reason I was to miss the game. It’s those life lessons that have brought me to where I am today.
The more I learned about the tech industry, the more I discovered how much it could be used for good.
How did you get into law?
I didn’t initially anticipate practicing law as a career. Entering college, I was set on a degree in education with a plan to teach high-school English, thanks to the influence of my primary school teachers.
While studying for my master’s in education, I became particularly interested in educational disparities, like why are some children afforded a better education and more resources than others? I began researching laws to educate myself and started to realize that a law degree could help me affect positive change. In some sense, I really fell into a law degree by virtue of following my passions and natural curiosity.
What shaped your interest in tech?
Technology, its importance and impact in the world, wasn’t something I spent much time thinking about while in Montana. Instead of video conferences and emails, I was picking up the phone to connect through a landline or showing up to have a cup of coffee.
But the more I learned about the tech industry, the more I discovered how much it could be used for good. I saw how this was the future and how it could connect my family and community to opportunities in a more equitable way. It’s why I participated in a Wi-Fi connectivity project with GAIN, Google’s Aboriginal and Indigenous Employee Resource Group. It’s how I found the ability to connect my education degrees to tech law. At Google, I’ve been able to do both.
How do you connect your work at Google to the causes you care about?
Giving back and engaging in community is critical in my life. Leaving the Blackfeet Indian Reservation in Montana is still something that pains me to this day. Leaving family has always been a challenge for me, but sharing my culture and raising awareness on issues facing Indigenous people has filled the void of missing home. Since joining Google, I’ve had the opportunity to provide awareness through various channels, including a Talks at Google interview with activist Kimberly Loring HeavyRunner and a Careers on Air virtual event celebrating Google’s Aboriginal and Indigenous communities.
Native Forward, the U.S.’s largest scholarship program for Native students with more than 16,000 recipients from over 500 Tribes, provided the funding to support my law school education. Recently, I was part of a group of Googlers who reviewed its scholarship applications, and I donate monthly via our internal platform that allows for company matching.
In addition to the work I do at Google, I also started a company, TPMOCS, in 2014, specializing in handcrafting children’s moccasins. We employ Native American artisans in rural communities and give a portion of profits to organizations on reservations supporting children in need.
Is there anything else you’d like to share?
During a trip back home to the Blackfeet Indian Reservation, I spent time with family and elders, and had a traditional naming ceremony for my children. I also had time to reflect on my life choices. Some, if given the chance, I would do over, but one that I’ve never second guessed is joining Google. As I speak at events, I’d like Indigeous youth and young professionals to know that you too can pursue a career in tech and still remain true to yourself. Representation matters and working at Google provides me with a platform to highlight interests and issues close to my heart. Google welcomes our voices.
From virtual classes to in-person lessons, the best learning environments may look different. But they have a few things in common: inspiring teachers, engaged students and a safe space to learn.
Over the last few years, spurred by COVID-19, millions of new users have come online to collaborate, create and learn. Because we support millions of education users every day, we think a lot about creating safe, digital-learning environments. It's only when users are safe online that learning can begin. It’s why our products are safe and secure by design, and why we continue to invest in this area.
We commissioned Forrester Consulting to conduct a Total Economic Impact study around Google Workspace for Education Plus, our most comprehensive edition of Google Workspace for Education. The study took a look at the security, administrative benefits and cost savings associated with it, and this is what it found: Education Plus helps reduce cyber threats, and the time to remediate them, for educational institutions worldwide.
Additionally, Forrester found organizations using Education Plus were more efficient in administration, and eliminated the need to invest in other education technology providers. You can download The Total Economic Impact Study to read the entire report, and we’ve included some highlights below:
Want to see how Education Plus could benefit your organization? Check out our new Education Plus Impact Calculator to calculate potential benefits and cost savings. Simply answer a set of 10 questions and you’ll receive a downloadable, custom impact report for your institution.
And whether you’re just learning about Education Plus or an existing customer, we’re announcing a new product demo experience for the premium features of Google Workspace for Education. Available to anyone, experience the real product interface and how your institution could use premium features including the investigation tool, security dashboard, advanced admin controls, Google Meet and originality reports.
Ready to create a safer digital learning experience for your school? Learn more and calculate the potential benefits and cost savings with our Education Plus Impact Calculator and product demo experience.
Whether it's a professional honing their skills or a child learning to read, coaches and educators play a key role in assessing the learner's answer to a question in a given context and guiding them towards a goal. These interactions have unique characteristics that set them apart from other forms of dialogue, yet are not available when learners practice alone at home. In the field of natural language processing, this type of capability has not received much attention and is technologically challenging. We set out to explore how we can use machine learning to assess answers in a way that facilitates learning.
In this blog, we introduce an important natural language understanding (NLU) capability called Natural Language Assessment (NLA), and discuss how it can be helpful in the context of education. While typical NLU tasks focus on the user's intent, NLA allows for the assessment of an answer from multiple perspectives. In situations where a user wants to know how good their answer is, NLA can offer an analysis of how close the answer is to what is expected. In situations where there may not be a “correct” answer, NLA can offer subtle insights that include topicality, relevance, verbosity, and beyond. We formulate the scope of NLA, present a practical model for carrying out topicality NLA, and showcase how NLA has been used to help job seekers practice answering interview questions with Google's new interview prep tool, Interview Warmup.
The goal of NLA is to evaluate the user's answer against a set of expectations. Consider the following components for an NLA system interacting with students:
With NLA, both the expectations about the answer and the assessment of the answer can be very broad. This enables teacher-student interactions that are more expressive and subtle. Here are two examples:
Context: Harry Potter and the Philosopher's Stone
Question: “What is Hogwarts?”
Expectation: “Hogwarts is a school of Witchcraft and Wizardry” [expectation is given as text]
Answer: “I am not exactly sure, but I think it is a school.”
The answer may be missing salient details but labeling it as incorrect wouldn’t be entirely true or useful to a user. NLA can offer a more subtle understanding by, for example, identifying that the student’s answer is too general, and also that the student is uncertain.
 |
| Illustration of the NLA process from input question, answer and expectation to assessment output |
This kind of subtle assessment, along with noting the uncertainty the student expressed, can be important in helping students build skills in conversational settings.
Question: “Tell me a little about yourself?”
Expectations: { “Education”, “Experience”, “Interests” } (a set of topics)
Answer: “Let’s see. I grew up in the Salinas valley in California and went to Stanford where I majored in economics but then got excited about technology so next I ….”
In this case, a useful assessment output would map the user’s answer to a subset of the topics covered, possibly along with a markup of which parts of the text relate to which topic. This can be challenging from an NLP perspective as answers can be long, topics can be mixed, and each topic on its own can be multi-faceted.
In principle, topicality NLA is a standard multi-class task for which one can readily train a classifier using standard techniques. However, training data for such scenarios is scarce and it would be costly and time consuming to collect for each question and topic. Our solution is to break each topic into granular components that can be identified using large language models (LLMs) with a straightforward generic tuning.
We map each topic to a list of underlying questions and define that if the sentence contains an answer to one of those underlying questions, then it covers that topic. For the topic “Experience” we might choose underlying questions such as:
While for the topic “Interests” we might choose underlying questions such as:
These underlying questions are designed through an iterative manual process. Importantly, since these questions are sufficiently granular, current language models (see details below) can capture their semantics. This allows us to offer a zero-shot setting for the NLA topicality task: once trained (more on the model below), it is easy to add new questions and new topics, or adapt existing topics by modifying their underlying content expectation without the need to collect topic specific data. See below the model’s predictions for the sentence “I’ve worked in retail for 3 years” for the two topics described above:
 |
| A diagram of how the model uses underlying questions to predict the topic most likely to be covered by the user’s answer. |
Since an underlying question for the topic “Experience” was matched, the sentence would be classified as “Experience”.
Interview Warmup is a new tool developed in collaboration with job seekers to help them prepare for interviews in fast-growing fields of employment such as IT Support and UX Design. It allows job seekers to practice answering questions selected by industry experts and to become more confident and comfortable with interviewing. As we worked with job seekers to understand their challenges in preparing for interviews and how an interview practice tool could be most useful, it inspired our research and the application of topicality NLA.
We build the topicality NLA model (once for all questions and topics) as follows: we train an encoder-only T5 model (EncT5 architecture) with 350 million parameters on Question-Answers data to predict the compatibility of an <underlying question, answer> pair. We rely on data from SQuAD 2.0 which was processed to produce <question, answer, label> triplets.
 |
| In the Interview Warmup tool, users can switch between talking points to see which ones were detected in their answer. |
The tool does not grade or judge answers. Instead it enables users to practice and identify ways to improve on their own. After a user replies to an interview question, their answer is parsed sentence-by-sentence with the Topicality NLA model. They can then switch between different talking points to see which ones were detected in their answer. We know that there are many potential pitfalls in signaling to a user that their response is “good”, especially as we only detect a limited set of topics. Instead, we keep the control in the user’s hands and only use ML to help users make their own discoveries about how to improve.
So far, the tool has had great results helping job seekers around the world, including in the US, and we have recently expanded it to Africa. We plan to continue working with job seekers to iterate and make the tool even more helpful to the millions of people searching for new jobs.
| A short film showing how Interview Warmup and its NLA capabilities were developed in collaboration with job seekers. |
Natural Language Assessment (NLA) is a technologically challenging and interesting research area. It paves the way for new conversational applications that promote learning by enabling the nuanced assessment and analysis of answers from multiple perspectives. Working together with communities, from job seekers and businesses to classroom teachers and students, we can identify situations where NLA has the potential to help people learn, engage, and develop skills across an array of subjects, and we can build applications in a responsible way that empower users to assess their own abilities and discover ways to improve.
This work is made possible through a collaboration spanning several teams across Google. We’d like to acknowledge contributions from Google Research Israel, Google Creative Lab, and Grow with Google teams among others.