We found 178 results that contain "test data"
Posted on: QA groups
Data communications
Data communications refers to the transmission of this digital data between two or more computers and a computer network or data network is a telecommunications network that allows computers to exchange data. The physical connection between networked computing devices is established using either cable media or wireless media. The best-known computer network is the Internet.
Posted on: QA groups
Data communications
Data communications refers to the transmission of this digital data between two or more computers and a computer network or data network is a telecommunications network that allows computers to exchange data. The physical connection between networked computing devices is established using either cable media or wireless media. The best-known computer network is the Internet.
Posted on: #iteachmsu
Data Science in Digital Marketing
The digital revolution is now sweeping small towns and villages perhaps driven by increased accessibility at affordable data costs? The whole world is in our hands and the increase in the usage of digital in rural India, where more than two-thirds of active internet users are present is a great opportunity and a win-win situation for both. They are trying to meet their entertainment and communication needs and we can help them provide the best of service in addition to winning their hearts and pocket.
ASSESSING LEARNING
Posted on: Software testing
Importance of Software Testing
It’s common for many startups to skip testing. They might say that their budget is the reason why they overlook such an important step. They think it would lead to no major consequences. But to make a strong and positive first impression, it needs to be top-notch. And for that, testing the product for bugs is a must.
To really understand why software testing is important, we need to correlate it with real world examples, which has caused serious issues in the past, a few examples include:
In October 2014, Flipkart an e-commerce in India company had an offer called the “Big Billion Sale.” When it was launched it had a lot of traffic and as a result, its website couldn’t handle the enormous load of traffic leading to the website downtime, cancellation of orders etc. The reputation of the organization was badly impacted by this issue.
In 2015, the Royal Bank of Scotland, due to a bug, couldn’t process about 600,000 payments. Because of this, they were fined 66 million pounds
Yahoo in September 2016, had a major data breach where 500 million users’ credentials got compromised.
To really understand why software testing is important, we need to correlate it with real world examples, which has caused serious issues in the past, a few examples include:
In October 2014, Flipkart an e-commerce in India company had an offer called the “Big Billion Sale.” When it was launched it had a lot of traffic and as a result, its website couldn’t handle the enormous load of traffic leading to the website downtime, cancellation of orders etc. The reputation of the organization was badly impacted by this issue.
In 2015, the Royal Bank of Scotland, due to a bug, couldn’t process about 600,000 payments. Because of this, they were fined 66 million pounds
Yahoo in September 2016, had a major data breach where 500 million users’ credentials got compromised.
Posted on: #iteachmsu
Five-second testing%
In a five-second test, you present your users with a design and give them five seconds to look at it, then ask them questions. This method can be used to test landing page copy, UI content, and more. You’re testing to see if the information on your page can be quickly absorbed, perceived, or understood.
The questions you ask can range from broad, like “What do you think of the page?” or “What do you remember seeing?” to more specific ones, like “Which of the items are on sale?”.
It’s best to start the test with broad questions to get general feedback and thoughts from your participants, then asking more specific questions to see what information stuck with them.
Preference testing
Preference testing consists of showing research participants two to three versions of your design—in this case, with variations in the content—to get an idea of which they prefer and why. It can help you understand the user’s perception of your content, how it makes them thin
The questions you ask can range from broad, like “What do you think of the page?” or “What do you remember seeing?” to more specific ones, like “Which of the items are on sale?”.
It’s best to start the test with broad questions to get general feedback and thoughts from your participants, then asking more specific questions to see what information stuck with them.
Preference testing
Preference testing consists of showing research participants two to three versions of your design—in this case, with variations in the content—to get an idea of which they prefer and why. It can help you understand the user’s perception of your content, how it makes them thin
NAVIGATING CONTEXT
Posted on: #iteachmsu
Five-second testing%
In a five-second test, you present your users with a design and give them five seconds to look at it, then ask them questions. This method can be used to test landing page copy, UI content, and more. You’re testing to see if the information on your page can be quickly absorbed, perceived, or understood.
The questions you ask can range from broad, like “What do you think of the page?” or “What do you remember seeing?” to more specific ones, like “Which of the items are on sale?”.
It’s best to start the test with broad questions to get general feedback and thoughts from your participants, then asking more specific questions to see what information stuck with them.
Preference testing
Preference testing consists of showing research participants two to three versions of your design—in this case, with variations in the content—to get an idea of which they prefer and why. It can help you understand the user’s perception of your content, how it makes them thin
The questions you ask can range from broad, like “What do you think of the page?” or “What do you remember seeing?” to more specific ones, like “Which of the items are on sale?”.
It’s best to start the test with broad questions to get general feedback and thoughts from your participants, then asking more specific questions to see what information stuck with them.
Preference testing
Preference testing consists of showing research participants two to three versions of your design—in this case, with variations in the content—to get an idea of which they prefer and why. It can help you understand the user’s perception of your content, how it makes them thin
NAVIGATING CONTEXT
Posted on: #iteachmsu
Importance of Software Testing
It’s common for many startups to skip testing. They might say that their budget is the reason why they overlook such an important step. They think it would lead to no major consequences. But to make a strong and positive first impression, it needs to be top-notch. And for that, testing the product for bugs is a must.
Posted on: #iteachmsu
Data availability
Just over 3 billion people are online with an estimated 17 billion connected devices or sensors. [9] That generates a large amount of data which, combined with decreasing costs of data storage, is easily available for use. Machine learning can use this as training data for learning algorithms, developing new rules to perform increasingly complex tasks.
Just over 3 billion people are online with an estimated 17 billion connected devices or sensors. That generates a large amount of data which, combined with decreasing costs of data storage, is easily available for use. Machine learning can use this as training data for learning algorithms, developing new rules to perform increasingly complex tasks.
Just over 3 billion people are online with an estimated 17 billion connected devices or sensors. [9] That generates a large amount of data which, combined with decreasing costs of data storage, is easily available for use. Machine learning can use this as training data for learning algorithms, developing new rules to perform increasingly complex tasks.
Just over 3 billion people are online with an estimated 17 billion connected devices or sensors. That generates a large amount of data which, combined with decreasing costs of data storage, is easily available for use. Machine learning can use this as training data for learning algorithms, developing new rules to perform increasingly complex tasks.
Just over 3 billion people are online with an estimated 17 billion connected devices or sensors. That generates a large amount of data which, combined with decreasing costs of data storage, is easily available for use. Machine learning can use this as training data for learning algorithms, developing new rules to perform increasingly complex tasks.
Just over 3 billion people are online with an estimated 17 billion connected devices or sensors. [9] That generates a large amount of data which, combined with decreasing costs of data storage, is easily available for use. Machine learning can use this as training data for learning algorithms, developing new rules to perform increasingly complex tasks.
Just over 3 billion people are online with an estimated 17 billion connected devices or sensors. That generates a large amount of data which, combined with decreasing costs of data storage, is easily available for use. Machine learning can use this as training data for learning algorithms, developing new rules to perform increasingly complex tasks.
Posted by: Chathuri Super admin..
Posted on: QA groups
Data communications
Data communications refers to the transmission of this digital data between two or more computers and a computer network or data network is a telecommunications network that allows computers to exchange data. The physical connection between networked computing devices is established using either cable media or wireless media. The best-known computer network is the Internet.
Posted by: Super Admin
Posted on: #iteachmsu
What Is Big Data? and How Big Data Works?
Big data:Big data refers to the large, diverse sets of information that grow at ever-increasing rates. It encompasses the volume of information, the velocity or speed at which it is created and collected, and the variety or scope of the data points being covered (known as the "three v's" of big data).
Big data is a great quantity of diverse information that arrives in increasing volumes and with ever-higher velocity.
Big data can be structured (often numeric, easily formatted and stored) or unstructured (more free-form, less quantifiable).
Nearly every department in a company can utilize findings from big data analysis, but handling its clutter and noise can pose problems.
Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins.
Big data is most often stored in computer databases and is analyzed using software specifically designed to handle large, complex data sets.
How Big Data Works
Big data can be categorized as unstructured or structured. Structured data consists of information already managed by the organization in databases and spreadsheets; it is frequently numeric in nature. Unstructured data is information that is unorganized and does not fall into a predetermined model or format. It includes data gathered from social media sources, which help institutions gather information on customer needs.
Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins. The presence of sensors and other inputs in smart devices allows for data to be gathered across a broad spectrum of situations and circumstances.
Big data is a great quantity of diverse information that arrives in increasing volumes and with ever-higher velocity.
Big data can be structured (often numeric, easily formatted and stored) or unstructured (more free-form, less quantifiable).
Nearly every department in a company can utilize findings from big data analysis, but handling its clutter and noise can pose problems.
Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins.
Big data is most often stored in computer databases and is analyzed using software specifically designed to handle large, complex data sets.
How Big Data Works
Big data can be categorized as unstructured or structured. Structured data consists of information already managed by the organization in databases and spreadsheets; it is frequently numeric in nature. Unstructured data is information that is unorganized and does not fall into a predetermined model or format. It includes data gathered from social media sources, which help institutions gather information on customer needs.
Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins. The presence of sensors and other inputs in smart devices allows for data to be gathered across a broad spectrum of situations and circumstances.
Authored by: Rupali
Posted on: #iteachmsu
Business Intelligence and Data Science
Business Intelligence and Data Science are two of the most recurring terms in the digital era. While both of them involve the use of data, they are totally different from one another. Data Science is the bigger pool containing greater information, BI can be thought of as a part of the bigger picture.
What is Business Intelligence?
Business Intelligence is a process of collecting, integrating, analyzing, and presenting the data. With Business Intelligence, executives and managers can have a better understanding of decision-making. This process is carried out through software services and tools.
Using Business Intelligence, organizations are able to several strategic and operational business decisions. Furthermore, BI tools are used for the analysis and creation of reports. They are also used for producing graphs, dashboards, summaries, and charts to help the business executives to make better decisions.
What is Business Intelligence?
Business Intelligence is a process of collecting, integrating, analyzing, and presenting the data. With Business Intelligence, executives and managers can have a better understanding of decision-making. This process is carried out through software services and tools.
Using Business Intelligence, organizations are able to several strategic and operational business decisions. Furthermore, BI tools are used for the analysis and creation of reports. They are also used for producing graphs, dashboards, summaries, and charts to help the business executives to make better decisions.
Authored by: Rupali
Assessing Learning
Posted on: #iteachmsu
Smoke test Article --edited
Smoke test Article
Primer text from The College of William & MaryADHD is one of the most commonly diagnosed conditions of children (Centers for DiseaseControl and Prevention, 2015).In a 2016 Centers for Disease Control and Prevention study, scientists found that 6.1 million children aged 2-17 years living in the U.S. had been diagnosed with attention-deficit/hyperactivity disorder (ADHD), which is similar to previous enAges 6-11: Approximately 2.4 million childrenAges 12-17: Approximately 3.3 million childrenThe diagnostic term attention deficit/hyperactivity disorder (ADHD) refers to individuals who display patterns of inattention, impulsivity, and overactive behavior that interfere with daily functioning (American Psychiatric Association [APA], 2013).The Diagnostic and Statistical Manual (DSM) V (APA, 2013) criteria for diagnosing ADHD listthree types of ADHD and the accompanying characteristics.
Primer text from The College of William & MaryADHD is one of the most commonly diagnosed conditions of children (Centers for DiseaseControl and Prevention, 2015).In a 2016 Centers for Disease Control and Prevention study, scientists found that 6.1 million children aged 2-17 years living in the U.S. had been diagnosed with attention-deficit/hyperactivity disorder (ADHD), which is similar to previous enAges 6-11: Approximately 2.4 million childrenAges 12-17: Approximately 3.3 million childrenThe diagnostic term attention deficit/hyperactivity disorder (ADHD) refers to individuals who display patterns of inattention, impulsivity, and overactive behavior that interfere with daily functioning (American Psychiatric Association [APA], 2013).The Diagnostic and Statistical Manual (DSM) V (APA, 2013) criteria for diagnosing ADHD listthree types of ADHD and the accompanying characteristics.
Authored by: Vija
Posted on: #iteachmsu
Careers for iGen'ers - You Need Either Skills or Education: Test article
Careers for iGen'ers - You Need Either Skills or Education
If you are iGen and looking for a career, please pick a major in fields where there will be plenty of jobs and avoid fields where the jobs are limited. Unless of course you are so different and truly one of a kind like: Michael Jordan, Prince, The Beatles, Albert Einstein, Bill Gates, Elon Musk, Kim Kardashian (just kidding).
You have two choices - pick a trade or get the right college education. Low skilled jobs will continue to disappear and you can not raise a family on the income from a low skilled job. You either need skills or education.
Healthcare and high tech are the booming fields now and that will continue for decades.
Thus careers in science, engineering, software, and medicine are a good choice.
There won't be many jobs for people who major in English, history, philosophy etc. Sorry.
If you want help choosing a new career, or making those big career decisions, check out my career counseling services.
Electrical Engineering and Software Engineering look really good. As does nursing, and being a family doctor.
Civil Engineering offers very few jobs since we are not building a lot of bridges and buildings. So avoid that.
Automotive engineering is tough. Not many US jobs except in the electric car field.
Jobs that must be done in person such as plumbers, electricians, barbers, beauticians, should still be in demand, although lower paying than jobs requiring a college education. The trades are more stable than many other careers.
Sales jobs will continue to shrink. Retails sales jobs are disappearing as shopping malls close and as Amazon takes over the world. Sales people are usually just middlemen. Who needs them? Sorry... However, sales people that do business development and find new customers are a different story. But the days of being a shoe salesman in a mall store are gone.
Business development and marketing are still good fields, but will see some unexpected changes.
The auto mechanic field is going to go through interesting changes with the growth of electric vehicles and self driving vehicles. EV's have less moving parts and fewer fluids to replace, but they still need tire changes.
Taxi driver jobs and truck driver jobs will start to experience less demand as automated vehicles take over. However, as of 2018, the demand for truck drivers is booming.
As automated electric vehicles take over, the need for individuals to own a car will be reduced. It will become more simple, less expensive, and more efficient to just walk outside, call up an app, have a driver-less Uber pick you up and take you to wherever you want to go. As long as a car can show up in 5 minutes or so, that will be the way to go. Owning your own car is not efficient, nor a good investment. Cars sit around doing nothing for 98% of their existence. They take up space, they consume your money on insurance and repairs even while they are just sitting doing nothing. How this will affect jobs, careers and the workplace will be interesting, and iGen'ers will be the first to experience this.
Space flight related jobs will pick up as we focus on getting people to the moon, Mars, and space stations.
Geology jobs, especially related to finding minerals on other planets should see a rise in demand.
Virtual Reality related jobs (whatever those are?) will pick up as VR technology becomes ubiquitous. Probably creating VR experiences will be popular.
The generation after the iGen'ers will be the ones who grow up thinking virtual reality is normal.
If you are iGen and looking for a career, please pick a major in fields where there will be plenty of jobs and avoid fields where the jobs are limited. Unless of course you are so different and truly one of a kind like: Michael Jordan, Prince, The Beatles, Albert Einstein, Bill Gates, Elon Musk, Kim Kardashian (just kidding).
You have two choices - pick a trade or get the right college education. Low skilled jobs will continue to disappear and you can not raise a family on the income from a low skilled job. You either need skills or education.
Healthcare and high tech are the booming fields now and that will continue for decades.
Thus careers in science, engineering, software, and medicine are a good choice.
There won't be many jobs for people who major in English, history, philosophy etc. Sorry.
If you want help choosing a new career, or making those big career decisions, check out my career counseling services.
Electrical Engineering and Software Engineering look really good. As does nursing, and being a family doctor.
Civil Engineering offers very few jobs since we are not building a lot of bridges and buildings. So avoid that.
Automotive engineering is tough. Not many US jobs except in the electric car field.
Jobs that must be done in person such as plumbers, electricians, barbers, beauticians, should still be in demand, although lower paying than jobs requiring a college education. The trades are more stable than many other careers.
Sales jobs will continue to shrink. Retails sales jobs are disappearing as shopping malls close and as Amazon takes over the world. Sales people are usually just middlemen. Who needs them? Sorry... However, sales people that do business development and find new customers are a different story. But the days of being a shoe salesman in a mall store are gone.
Business development and marketing are still good fields, but will see some unexpected changes.
The auto mechanic field is going to go through interesting changes with the growth of electric vehicles and self driving vehicles. EV's have less moving parts and fewer fluids to replace, but they still need tire changes.
Taxi driver jobs and truck driver jobs will start to experience less demand as automated vehicles take over. However, as of 2018, the demand for truck drivers is booming.
As automated electric vehicles take over, the need for individuals to own a car will be reduced. It will become more simple, less expensive, and more efficient to just walk outside, call up an app, have a driver-less Uber pick you up and take you to wherever you want to go. As long as a car can show up in 5 minutes or so, that will be the way to go. Owning your own car is not efficient, nor a good investment. Cars sit around doing nothing for 98% of their existence. They take up space, they consume your money on insurance and repairs even while they are just sitting doing nothing. How this will affect jobs, careers and the workplace will be interesting, and iGen'ers will be the first to experience this.
Space flight related jobs will pick up as we focus on getting people to the moon, Mars, and space stations.
Geology jobs, especially related to finding minerals on other planets should see a rise in demand.
Virtual Reality related jobs (whatever those are?) will pick up as VR technology becomes ubiquitous. Probably creating VR experiences will be popular.
The generation after the iGen'ers will be the ones who grow up thinking virtual reality is normal.
Authored by: Chathuri
Pedagogical Design
Posted on: #iteachmsu
A Case for More Testing: The Benefits of Frequent, Low-Stakes Assessments
What if I told you about this magical teaching practice that, done even once, produces large improvements in student final exam scores[1], helps narrow the grade gap between poorly prepped and highly prepped first year college students[2], and might even result in more positive course reviews[3],[4]? What if I also told you this magical teaching practice is something you already know how to do? What if I told you, the secret to increasing your students’ success and overall satisfaction is……more TESTS!?
Okay…well to be fair, it’s a little more nuanced than that. While adding just one test to a class does indeed improve final exam scores, it turns out that more frequent, graded exercises in general improve learning outcomes for students [2],[5]. Even better – if these exercises are low stakes, they can improve learning outcomes without increasing student anxiety [4],[6].
We often view testing as an unpleasant but necessary way to assess student performance. It may be time for us to instead view testing as a useful teaching tool and to implement an assessment system that maximizes the potential learning benefits. In this post I will discuss the important known benefits of frequent, low stakes assessments as well as some practical tips for how to maximize these benefits without adding undue stress to your life or the lives of your students.
Benefit #1: “Thinking about thinking”
Testing can improve a student’s metacognition, or their ability to “think about thinking.” A good metacognitive thinker understands how their thought processes work and can pay attention to and change these processes [7]. A student with strong metacognitive skills can therefore more successfully monitor, evaluate, and improve their learning compared to students lacking these skills. Unfortunately, many students struggle with metacognition and must contend with “illusions of mastery” (or thinking they understand a subject better than they actually do). Self-testing is a good way to prevent illusions of mastery, but many students do not incorporate self-testing into their studying, instead electing more passive modes of exam preparation such as rereading texts[8]. Incorporating more testing into the curriculum forces students into the position of making mistakes and receiving feedback, allowing them to frequently measure their learning in relation to expectations and adjust accordingly. Again, note that providing feedback is an essential part of this process.
Benefit #2: Practice Remembering
Testing can improve a student’s long term memory of information presented in class by forcing students to recall what they’ve learned through a cognitive process called active retrieval. Active retrieval strengthens neural pathways important for retrieving memories, allowing these memories to be more easily accessed in the future.
While any sort of retrieval practice is useful, it is most beneficial when it is effortful, spaced, and interleaved. An example of effortful retrieval practice includes testing which forces students to provide the answers (i.e. Short answer and fill in the blank questions as opposed to multiple choice). More effortful retrieval also occurs with spaced and interleaved practice.
Spaced practice is testing that occurs after enough time has elapsed for some (but not complete) forgetting to occur (i.e. Present the information and then wait a couple months, days, or even just until the end of class to test students on it). Interleaved practice incorporates different but related topics and problem types, as opposed to having students practice and master one type at a time (e.g. cumulative testing where you mix problems from different units together). Interleaved practice can help students learn to focus on the underlying principles of problems and to discriminate between problem types, leading to more complex mental models and a deeper understanding of the relationships between ideas[6].
How to Implement More Assessments (Without Losing Your Mind)
So, all you have to do now is come up with a ton of quiz and test questions and free up a bunch of class time for assessments! Don’t forget you also need to grade all of these! After all, feedback is an important part of the process, and frequent (even low stakes) grading has the added benefits of enhancing student motivation, attentiveness, and attendance.I know what you busy teachers (ie. all of you) out there are thinking….“Your ”magical” teaching practice is starting to sound like a hugely effective pain in my butt.”
Don’t give up on me now though! There are some fairly simple ways to add more assessments to your curriculum. Furthermore, you should be able to do this sans student rebellion because these assessments are low-stakes. Frequent, low-stake assessments as opposed to infrequent, high-stakes assessments actually decrease student anxiety overall because no single test is a make it or break it event. In fact, several teachers have reported a large increase in positive student evaluations after restructuring their classes in this way[3],[4],[6]!
Below I lay out some tips for getting the most out of shifting your assessment practices while maintaining both your own and your students’ sanity:
1) Know that “effortful” testing is not always necessary
While effortful testing is best for retrieval practice, even basic, easily graded recognition tests such multiple choice questions still offer benefits, such as helping students remember basic (but important!) information[6],[9].
2) Create different assessment questions
You can also make assessments more effortful by creating questions that engage higher cognitive processes. Now you can sit back, relax, and indulge in one of my personal favorite pastimes (watching student brains explode) without the stressful grading!
3) Make use of educational technologies to ease your grading
For instance, clicker tests are a quick way to test students and allow you to provide feedback for the class all at once.
4) Make assessments into games
If your students need a morale boost, make a quiz into a trivia game and give winning groups candy. Some good old competition and Pavlovian conditioning may make students reassess their view of testing.
5) Assess participation
Doing something as simple as a participation grade will still provide students with incentive without overburdening them or yourself. For instance, this type of grading would work in conjunction with #3.
6) Keep graded assessments predictable
Making assessments predictable as opposed to utilizing pop quizzes helps students feel at ease.6 Furthermore, if they students KNOW an assessment is coming, they are more likely to study and pay attention.
7) Find ways to revisit old material in your assessments
Making assessments cumulative is an effective way to space out your review of material and has the added benefit of making problems interleaved and effortful, all of which maximize retrieval practice[6].
8) Have students reflect on mistakes
You can help students develop metacognitive skills by giving them opportunities to reflect upon and correct their mistakes on assessments. For instance, have students take a quiz and then discuss their answers/thinking with their classmates before receiving feedback. You can also give students opportunities to create keys to short answer questions and grade their own and several (anonymous) classmates’ answers. This will allow them to think through what makes an answer complete and effective.
9) Break large assessments into small ones
Instead of creating new assessments, break up large ones into multiple, lower-stakes assessments. For example, consider replacing big tests with several quizzes. Consider scaffolding large projects such as independent research projects and term papers. Ask for outlines, lists of references, graphs, etc. along the course of the semester before the final project is due. This might cause more work for you in the short term but can help prevent complete disasters at the end of the semester, which can be time consuming.
10) Utilize short daily or weekly quizzes
If you don’t want to adjust a big project/test or lose class time by adding time-consuming assessments, consider adding short daily or weekly quizzes. These grades can add up to equal one test grade. One could consider dropping the lowest score(s) but allowing no make ups to reduce logistical issues.
These are only a few of the many strategies one can use to transition to a frequent, low-stakes assessment system. What are your experiences with low stakes assessments? Have you made use of any which seem particularly effective in enhancing student learning?
Related Reading:
Much of the information about the benefits of testing is from:
Brown, P.C., Roediger III, H.L., McDaniel, M.A. (2014). Make it Stick: The Science of Successful Learning. Cambridge, MA: The Belknap Press of Harvard University Press.
Okay…well to be fair, it’s a little more nuanced than that. While adding just one test to a class does indeed improve final exam scores, it turns out that more frequent, graded exercises in general improve learning outcomes for students [2],[5]. Even better – if these exercises are low stakes, they can improve learning outcomes without increasing student anxiety [4],[6].
We often view testing as an unpleasant but necessary way to assess student performance. It may be time for us to instead view testing as a useful teaching tool and to implement an assessment system that maximizes the potential learning benefits. In this post I will discuss the important known benefits of frequent, low stakes assessments as well as some practical tips for how to maximize these benefits without adding undue stress to your life or the lives of your students.
Benefit #1: “Thinking about thinking”
Testing can improve a student’s metacognition, or their ability to “think about thinking.” A good metacognitive thinker understands how their thought processes work and can pay attention to and change these processes [7]. A student with strong metacognitive skills can therefore more successfully monitor, evaluate, and improve their learning compared to students lacking these skills. Unfortunately, many students struggle with metacognition and must contend with “illusions of mastery” (or thinking they understand a subject better than they actually do). Self-testing is a good way to prevent illusions of mastery, but many students do not incorporate self-testing into their studying, instead electing more passive modes of exam preparation such as rereading texts[8]. Incorporating more testing into the curriculum forces students into the position of making mistakes and receiving feedback, allowing them to frequently measure their learning in relation to expectations and adjust accordingly. Again, note that providing feedback is an essential part of this process.
Benefit #2: Practice Remembering
Testing can improve a student’s long term memory of information presented in class by forcing students to recall what they’ve learned through a cognitive process called active retrieval. Active retrieval strengthens neural pathways important for retrieving memories, allowing these memories to be more easily accessed in the future.
While any sort of retrieval practice is useful, it is most beneficial when it is effortful, spaced, and interleaved. An example of effortful retrieval practice includes testing which forces students to provide the answers (i.e. Short answer and fill in the blank questions as opposed to multiple choice). More effortful retrieval also occurs with spaced and interleaved practice.
Spaced practice is testing that occurs after enough time has elapsed for some (but not complete) forgetting to occur (i.e. Present the information and then wait a couple months, days, or even just until the end of class to test students on it). Interleaved practice incorporates different but related topics and problem types, as opposed to having students practice and master one type at a time (e.g. cumulative testing where you mix problems from different units together). Interleaved practice can help students learn to focus on the underlying principles of problems and to discriminate between problem types, leading to more complex mental models and a deeper understanding of the relationships between ideas[6].
How to Implement More Assessments (Without Losing Your Mind)
So, all you have to do now is come up with a ton of quiz and test questions and free up a bunch of class time for assessments! Don’t forget you also need to grade all of these! After all, feedback is an important part of the process, and frequent (even low stakes) grading has the added benefits of enhancing student motivation, attentiveness, and attendance.I know what you busy teachers (ie. all of you) out there are thinking….“Your ”magical” teaching practice is starting to sound like a hugely effective pain in my butt.”
Don’t give up on me now though! There are some fairly simple ways to add more assessments to your curriculum. Furthermore, you should be able to do this sans student rebellion because these assessments are low-stakes. Frequent, low-stake assessments as opposed to infrequent, high-stakes assessments actually decrease student anxiety overall because no single test is a make it or break it event. In fact, several teachers have reported a large increase in positive student evaluations after restructuring their classes in this way[3],[4],[6]!
Below I lay out some tips for getting the most out of shifting your assessment practices while maintaining both your own and your students’ sanity:
1) Know that “effortful” testing is not always necessary
While effortful testing is best for retrieval practice, even basic, easily graded recognition tests such multiple choice questions still offer benefits, such as helping students remember basic (but important!) information[6],[9].
2) Create different assessment questions
You can also make assessments more effortful by creating questions that engage higher cognitive processes. Now you can sit back, relax, and indulge in one of my personal favorite pastimes (watching student brains explode) without the stressful grading!
3) Make use of educational technologies to ease your grading
For instance, clicker tests are a quick way to test students and allow you to provide feedback for the class all at once.
4) Make assessments into games
If your students need a morale boost, make a quiz into a trivia game and give winning groups candy. Some good old competition and Pavlovian conditioning may make students reassess their view of testing.
5) Assess participation
Doing something as simple as a participation grade will still provide students with incentive without overburdening them or yourself. For instance, this type of grading would work in conjunction with #3.
6) Keep graded assessments predictable
Making assessments predictable as opposed to utilizing pop quizzes helps students feel at ease.6 Furthermore, if they students KNOW an assessment is coming, they are more likely to study and pay attention.
7) Find ways to revisit old material in your assessments
Making assessments cumulative is an effective way to space out your review of material and has the added benefit of making problems interleaved and effortful, all of which maximize retrieval practice[6].
8) Have students reflect on mistakes
You can help students develop metacognitive skills by giving them opportunities to reflect upon and correct their mistakes on assessments. For instance, have students take a quiz and then discuss their answers/thinking with their classmates before receiving feedback. You can also give students opportunities to create keys to short answer questions and grade their own and several (anonymous) classmates’ answers. This will allow them to think through what makes an answer complete and effective.
9) Break large assessments into small ones
Instead of creating new assessments, break up large ones into multiple, lower-stakes assessments. For example, consider replacing big tests with several quizzes. Consider scaffolding large projects such as independent research projects and term papers. Ask for outlines, lists of references, graphs, etc. along the course of the semester before the final project is due. This might cause more work for you in the short term but can help prevent complete disasters at the end of the semester, which can be time consuming.
10) Utilize short daily or weekly quizzes
If you don’t want to adjust a big project/test or lose class time by adding time-consuming assessments, consider adding short daily or weekly quizzes. These grades can add up to equal one test grade. One could consider dropping the lowest score(s) but allowing no make ups to reduce logistical issues.
These are only a few of the many strategies one can use to transition to a frequent, low-stakes assessment system. What are your experiences with low stakes assessments? Have you made use of any which seem particularly effective in enhancing student learning?
Related Reading:
Much of the information about the benefits of testing is from:
Brown, P.C., Roediger III, H.L., McDaniel, M.A. (2014). Make it Stick: The Science of Successful Learning. Cambridge, MA: The Belknap Press of Harvard University Press.
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Big data is a collection of large datasets that cannot be processed using traditional computing techniques. Testing of these datasets involves various tools, techniques and frameworks to process. Big data relates to data creation, storage, retrieval and analysis that is remarkable in terms of volume, variety, and velocity. You can learn more about Big Data, Hadoop and Mapreduce here In this tutorial we will learn, Testing Big Data application is more a verification of its data processing rather than testing the individual features of the software product. When it comes to Big data testing, performance and functional testing are the key. In Big data testing QA engineers verify the successful processing of terabytes of data using commodity cluster and other supportive components. It demands a high level of testing skills as the processing is very fast. Processing may be of three types Along with this, data quality is also an important factor in big data testing. Before testing the application, it is necessary to check the quality of data and should be considered as a part of database testing. It involves checking various characteristics like conformity, accuracy, duplication, consistency, validity, data completeness, etc.
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Data communications refers to the transmission of this digital data between two or more computers and a computer network or data network is a telecommunications network that allows computers to exchange data. The physical connection between networked computing devices is established using either cable media or wireless media. The best-known computer network is the Internet.
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Data Science::
Data Science is a comprehensive process that involves preprocessing, analysis, visualization, and prediction. On the other hand, AI is the implementation of a predictive model to forecast future events.
A Data Scientist, on the other hand, helps the company and businesses to make careful data-driven decisions. A Data Scientist is responsible for extracting data using SQL and NoSQL queries, cleaning various anomalies in the data, analyzing the patterns in data, and applying predictive models.
Data Science is a comprehensive process that involves preprocessing, analysis, visualization, and prediction. On the other hand, AI is the implementation of a predictive model to forecast future events.
A Data Scientist, on the other hand, helps the company and businesses to make careful data-driven decisions. A Data Scientist is responsible for extracting data using SQL and NoSQL queries, cleaning various anomalies in the data, analyzing the patterns in data, and applying predictive models.
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Assessing Learning
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Big data is more than high-volume, high-velocity data. Learn what big data is, why it matters and how it can help you make better decisions every day.
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Disciplinary Content
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Data Science is a process of extracting, manipulating, visualizing, maintaining data as well as generating predictions.
A Data Scientist is supposed to have knowledge of various data operations as well as machine learning algorithms. Using Data Science, industries are able to extract insights and forecast their performance.
A Data Scientist is supposed to have knowledge of various data operations as well as machine learning algorithms. Using Data Science, industries are able to extract insights and forecast their performance.
Posted by: Chathuri Super admin..
Assessing Learning
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Machine-generated data is information automatically generated by a computer process, application, or other mechanism without the active intervention of a human. While the term dates back over fifty years,[1] there is some current indecision as to the scope of the term. Monash Research's Curt Monash defines it as "data that was produced entirely by machines OR data that is more about observing humans than recording their choices."[2] Meanwhile, Daniel Abadi, CS Professor at Yale, proposes a narrower definition, "Machine-generated data is data that is generated as a result of a decision of an independent computational agent or a measurement of an event that is not caused by a human action."[3] Regardless of definition differences, both exclude data manually entered by a person.[4] Machine-generated data crosses all industry sectors. Often and increasingly, humans are unaware their actions are generating the data.[
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Assessing Learning
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Big data is more than high-volume, high-velocity data. Learn what big data is, why it matters and how it can help you make better decisions every day
Big data is more than high-volume, high-velocity data. Learn what big data is, why it matters and how it can help you make better decisions every day
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Disciplinary Content
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Data Science is a field that makes use of scientific methods and algorithms in order to extract knowledge and discover insights from data (structured on unstructured). Data Analytics is the process of using specialized systems and software to inspect information in datasets in order to derive conclusions
Posted by: Rupali Jagtap
Assessing Learning
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Best Practices in Data Visualization
Learn general best practices for creating data visualizations. This workshop will describe the overarching goals of data visualization and provide criteria for evaluating the effectiveness of a visualization. This workshop will also offer tool suggestions for beginners exploring data visualization.
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Data Management Plans: Yes, you need one and here is how to create them
An overview of why data management plans are important and often required, and how to develop one. We will look at the items commonly included in all data management plans regardless of agency/institutional requirements, some examples of specific funding agency templates and review what resources are available to help you draft your plan.
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Research Data Management: Best Practices for organizing and managing your data
Why is research data management so important? This workshop will help you plan for organizing and managing your data from the outset of your project.
We will look at some basic best practices for:
organizing your data
cleaning/prepping/working with your data
working with multiple data files
storage solutions
long-term archiving and making your data accessible to other researchers
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3D Terrain Elevation Models for 3D Printing (Online)
Learn how to produce a 3D model of terrain elevation for printing on a 3D printer. We will learn about 3D models for 3D printing, digital elevation models (DEMs), where to find DEM data to create our printable export, and then use a plug in DEMto3D in the open source software QGIS to create a model. If time allows, basic tools for 3D model editing in Meshmixer or slicing software will be demonstrated.
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Intro to 360 Cameras, 3D Scanners, & Other Digitization Equipment @ DSL: Drop-in Session
Immersive data is everywhere. It's in every digital asset you see in a video game, a YouTube 360 video and the panoramic pictures you take with your mobile device. Drop in to learn about how 360 cameras, 3D scanners and our digitization equipment is used to create these new experiences and apply them to your research, assignments and presentations.
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Learn QGIS: Making a color shaded map in QGIS (Online)
Learn the basics of QGIS, the free open-source geospatial software—this workshop will demonstrate how to make a choropleth (color shaded) map and place graduated symbols representing data on it, load shape-files and .csv table files into QGIS, join data to spatial information and edit features. No experience with QGIS or Geographic Information Systems is required.
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Intro to Anatomage @ DSL: Drop-In Session
Come learn about the Anatomage Table! The Anatomage Table is the only fully segmented real human 3D anatomy platform, and you can drop in to check out, test it out, and think about how you can use it for your curriculum, courses, research support, and to enhance the student experience.
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Computer Fundamentals
Computer is an advanced electronic device that takes raw data as an input from the user and processes it under the control of a set of instructions (called program), produces a result (output), and saves it for future use. This tutorial explains the foundational concepts of computer hardware, software, operating systems, peripherals, etc. along with how to get the most value and impact from computer technology.