Do PhD students get the right support from universities? | Times Higher Education

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Follow on Twitter as @jgro_the

"Feelings of stress, self-doubt and isolation can affect even the brightest and most assured PhD student" summarizes Jack Grove, reporter covering teaching and learning, quality assurance, student affairs and access to higher education for Times Higher Education. 

Lean on me: some institutions have set up doctoral colleges to create a more supportive environment for PhD students.
Photo: Alamy

So are universities doing enough to support students on the long slog towards a doctorate? And do new PhD students get the same level of help as the 500,000 or so first-year undergraduates arriving on campus each autumn?

Those questions were recently asked by staff at the University of Nottingham, leading to a review of how the institution helps its doctoral students, particularly those in the early stages of their research.
Parmjit Dhugga, head of researcher development at the university’s graduate school, said that a renewed national focus on stress suffered by graduate students prompted Nottingham to assess the relevancy of its own pastoral support.

While just 15 per cent of 760 doctoral students who responded to Nottingham’s survey reported any significant difficulty making the transition into graduate study, the problems raised were often very different from those usually cited by undergraduates and required different interventions, said Mr Dhugga.

“Some spoke of a lack of progress in their research topic, awkward relationships with their supervisor and a sense of isolation, even when they were based in a research group,” he added.

Some PhD students also mentioned stress caused by long hours of study as aspiring scholars sought to outdo their older academic peers, Mr Dhugga said.

“They saw their colleagues working very hard and think they need to equal these long hours as that’s just part of academic life,” he explained.

Indeed, many doctoral students felt their problems were closer to those experienced by academic staff, rather than undergraduates or even taught postgraduates, said Mr Dhugga, who will explain how Nottingham is changing its doctoral support set-up in a talk at the UK Council for Graduate Education’s annual conference, which takes place in Liverpool from 4 to 5 July.

Identity indecision 
“Doctoral students often don’t see themselves as students, so they are not sure whether to turn to staff or student support,” he said.

Nottingham’s investigation is part of a wider push by the sector to develop new structures and services to support doctoral students, of whom about a quarter will not finish their studies, latest figures suggest.
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Photo: Joanna Williams

Is there a problem with academic integrity? by Joanna William, part-time senior lecturer in higher education at the University of Kent.
A survey suggests research misconduct in the UK is higher than previously feared. Joanna Williams and five other academics ponder the results. 

Source: Times Higher Education

Educators Deliver Mixed Reviews of High School Mathematics Materials | EdReports (Press Releases)

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The curriculum review website EdReports.org released its first round of results for high school math textbooks.

EdReports.org, the nonprofit whose educator teams review instructional materials to determine alignment to Common Core standards, announced the results of its first round of reviews of high school mathematics textbooks. Five reports examining both three-course traditional (Algebra I, Geometry, Algebra II) and integrated (I, II, III) sequences were published today, along with the review tool and evidence guides educators used in the process. 

Photo: FreeDigitalPhotos.net

Of the five reports, one series – Core Connections (CPM) – met criteria for alignment in all three review gateways.

“When we launched EdReports a year ago with our first round of reviews, we were overwhelmed by the response,” said Eric Hirsch, executive director of EdReports. “It was clear the community was hungry for our freely available, evidence-based reports, and educators were clamoring for information on what materials can best serve their classrooms. We see this need not only in the elementary and middle school grades but in high school, as well. I am delighted we have been able to respond to the demand with more evidence and more reviews.”

Reviewers noted positive evidence that can benefit teachers and students across all of the series. Highlights from the first round of high school reviews include: 

• Core Connections (CPM) (traditional): Met Expectations for Gateway 1, Gateway 2 and Gateway 3
• Carnegie Learning (traditional): Partially Met Expectations for Gateway 1 and Gateway 2 
• Houghton Mifflin Harcourt (traditional): Did Not Meet Expectations for Gateway 1 
• Pearson (integrated): Did Not Meet Expectations for Gateway 1 
• Springboard College Board (traditional): Did Not Meet Expectations for Gateway 1

EdReports educators review materials based on criteria that measure alignment to the Common Core State Standards. The review tool for high school math, developed by the educators, shares characteristics with the K-8 math tool. One key similarity is that the tool supports a sequential review process, or review by gateways. Reviewers consider: Gateway 1) focus and coherence; Gateway 2) rigor and mathematical practices; and Gateway 3) instructional supports and other usability indicators.
 
Reviewers first ensure all of the high school standards are addressed in the series and that the materials make strong connections between the mathematical content, as opposed to teaching skills and concepts in isolation (focus and coherence). Only if materials meet or partially meet these criteria do reviewers then consider the rigor of the materials and evaluate connections to the mathematical practices. Finally, if the criteria for these first two gateways are at least partially met, the materials are reviewed for usability.
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Source: EdReports (Press Releases)

The Internet of Things: Riding the Wave in Higher Education | EDUCAUSE Review

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Looking at the vast ocean that is modern-day computing, we can see that major developments come in waves. The arrival of mainframe computers in the 1960s generated the first wave (one computer for many people), followed in the late 1970s by personal computers in the second wave (one computer for one person). 

In 1988, Mark Weiser presciently observed that computers embedded into everyday objects, objects all around us, were forming the third wave—what he called ubiquitous computing (many computers for one person). A decade later, in 1999, Keven Ashton put forth the ideas behind, and coined the term for, the fourth wave: the Internet of Things. 

In this paradigm shift, Weiser's computer-embedded everyday objects—or "things"—are connected to the Internet and can communicate with users and with other devices. The guiding principle is connection, along with the conviction that if something can be connected, it will be connected. Indeed, in recent years, the wave appears to be rising to a crest. The plunging cost and size of processors and chipsets, the massive expansion of the IP address space, and the growing coverage of broadband networks allow virtually any object to be connected to the Internet. The computers, laptops, tablets, and smartphones that constitute the bulk of the Internet of Things (IoT) today are being joined by smartwatches, smart appliances, cars, lightbulbs, and an array of other devices that collect and transfer data, often without any human involvement. As that data is increasing and the technologies are advancing, we are moving from the early IoT of smart connections to a new phase, one of invisible integration...

Below, five industry leaders give their perspectives on the IoT and new devices; the IoT benefits and campus influence; the problems solved/created by the IoT; and security, privacy, and data-ownership issues. Based on their experiences with the IoT, they also share lessons learned and offer words of wisdom.

Photo: Itai Asseo, 
Strategic Innovation
 Executive Salesforce

The Internet of Things has evolved over many decades as wearables, RFID, BYOD, wireless devices, and more have increased in both number and usage. How do you define the IoT today?
The Internet of Things is not a new term. It's been around since at least the late 1990s, but another decade or so went by before it became a mainstream term. The idea is that as computing power can be condensed into ever smaller units and devices, and as the power demand gets lower and more efficient, we can embed computing devices into anything from household items to clothing—and even into living matter...

Photo: Maggie Johnson,
Director of Education
and University Relations
Google

The Internet of Things has evolved over many decades as wearables, RFID, BYOD, wireless devices, and more have increased in both number and usage. How do you define the IoT today?
At Google, we define the IoT as a network of everyday items with embedded computers that can connect directly or indirectly to the Internet. The number of devices connecting to the Internet is likely to grow exponentially over the next ten years...  

Photo:Bob Nilsson,
Director of Solutions
Marketing Extreme Networks

The Internet of Things has evolved over many decades as wearables, RFID, BYOD, wireless devices, and more have increased in both number and usage. How do you define the IoT today?
The phrase Internet of Things (IoT) generally refers to machine-to-machine (M2M) communications involving network-based remote sensors and actuators. Wireless sensors generate data (often "big data"), which can be stored and analyzed either on site or in the cloud. The range of smart IoT devices found in schools today includes e-books and tablets; sensors in hallways, entrances, classroom spaces, and campus vehicles; all sorts of fitness bands and wearables; virtual and augmented reality headsets; robots; video sensors; and smart displays, lights, and locks. Data from these devices can be used for simple tracking (e.g., campus shuttles, student attendance, and supplies) or for more complex monitoring (e.g., to understand student learning patterns as students progress through e-books and adaptive learning systems). Data can also be used for control. For example, the IoT provides the means to finely tune HVAC systems to keep all rooms throughout the campus optimally comfortable at minimum expense. Airflow, air quality, temperature, humidity, and lighting can be constantly optimized in every space that can conceivably be used for learning. Finally, flexible displays provide the important benefit of easily presenting data and status information on classroom screens or personal devices like smartphones and laptops...  

Photo:Chalapathy Neti,
 Vice President, Education
Innovation, IBM

The Internet of Things has evolved over many decades as wearables, RFID, BYOD, wireless devices, and more have increased in both number and usage. How do you define the IoT today?
The IoT is changing everything—from the way we drive, make purchases, and obtain medical treatment, to how we get energy for our homes. Data is emanating from everywhere. IDC predicts that by 2020, there will be close to 30 billion connected devices.¹ Today we define the IoT not only by its ability to connect devices (vehicles, buildings, wearables, and more) to a digital network, but also by its ability to directly integrate the physical world into computer-based systems. It is how people interact with this network of things that has become most interesting as the IoT has evolved...

Photo: TJ Costello,
Director IoT
Cisco U.S. Public Sector

What are the most exciting academic and administrative benefits enabled by the IoT for higher education?   
The IoT opens a range of possibilities and benefits for faculty, staff, and students. With the IoT, students are able to attend any class, at any time, from any device—providing them with greater flexibility to consume content and knowledge when and where they'd like. The IoT removes the traditional barriers to teaching and learning, providing faculty with the same flexibility to provide better learning experiences for students and allowing them to connect with experts from around the world and create robust, hybrid learning environments. The IoT also benefits administrators by helping to connect everything on campus everywhere through one secure, unified network to manage campus lighting, parking, HVAC systems, and cameras and to provide valuable data and analytics on traffic patterns, usage, and areas of resource optimization.
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Photo: John O'Brien

"For the Internet of Things to add value to the world of higher education, unprecedented collaboration between all those involved will be crucial."

The Internet of Things: Unprecedented Collaboration Required by John O'Brien, president and CEO of EDUCAUSE.
Read as PDF
 
Source: EDUCAUSE Review

In Terms of Assessment, Teachers Know Best | Education Week

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Jessica Potts, teaches online history and English middle school courses at The Davidson Academy and Skip Potts,Skip Potts, director of The Language House writes, "It seems as if no discussion of America's educational climate is complete without the mention of Carol Dweck's concept of "growth mindset" and Angela Duckworth's notion of "grit." Along with the fervor surrounding these buzzwords comes the inevitable calls for some sort of quantifiable measurement of these largely intangible characteristics." 

Photo: Getty

And although both Dweck and Duckworth largely disavow the notion of measuring these intangible skills, their respective websites offer a visitor the opportunity to test these soft skills. And in the past three years alone, hundreds of academic articles have been written about growth-mindset and grit skills, including in Education Week.

Forgetting for a moment the larger debate about the validity or newness of some of these "innovations," their measurement specifically should be looked at with a critical eye. Growth mindset and grit are understandably difficult to measure using standardized methods and instead often rely on Likert-style self-reporting. As some critics have noted, such surveys can be muddy and vulnerable to biases. The 2012 Program for International Student Assessment results place American schoolchildren 27th in math and 20th in science but far above average in confidence, suggesting that self-reporting as a method is inherently problematic, particularly in the United States. In fact, many of the psychological measures currently used are unreliable and subject to reference bias, confirmation bias, and social-desirability bias. Therefore, if we do want to find viable ways to evaluate grit or mindset, where do we look for our solutions?

In this age of educational accountability, the knee-jerk reaction is for policymakers to measure these delicate values through some type of box-checking scheme. Before we discuss the potential of this particular endeavor, it would be instructive to examine historical attempts to translate natural human behaviors into mechanical, quantifiable systems. Consider the famous walking robots of Boston Dynamics. Boston Dynamics, an MIT-spawned company that focuses on robotics and human-simulation software, attempted to create a robot that could effectively mimic the human gait. This company, which employed the brightest minds of the Massachusetts Institute of Technology, was funded by the Defense Advanced Research Projects Agency, or DARPA, and later bought by Google. It had all the money, intelligence, and support it could possibly need, and it still took more than a decade to get its first real success with the BigDog robot in 2005.
Read more...

Source: Education Week

Faculty Mentoring Undergraduates: The Nature, Development, and Benefits of Mentoring Relationships | Faculty Focus

Editor’s Note: This is an excerpt of a work that is licensed under a Creative Commons Attribution 4.0 International License. To read the article in its entirety, visit the Teaching & Learning Inquiry website.

Reference: McKinsey, E. (2016). Faculty Mentoring Undergraduates: The Nature, Development, and Benefits of Mentoring Relationships. Teaching & Learning Inquiry, 4(1), 1-15. doi: http://dx.doi.org/10.20343/teachlearninqu.4.1.5 

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Photo: Elizabeth McKinsey

Elizabeth McKinsey, teaches in both English and American Studies reports, "Educational research shows that close student-faculty interaction is a key factor in college student learning and success. Most literature on undergraduate mentoring, however, focuses on planned programs of mentoring for targeted groups of students by non-faculty professionals or student peers."

Photo: Faculty Focus

Based on the research literature and student and faculty testimony from a residential liberal arts college, this article shows that unplanned “natural” mentoring can be crucial to student learning and development and illustrates some best practices. It advances understanding of faculty mentoring by differentiating it from teaching, characterizing several functional types of mentoring, and identifying the phases through which a mentoring relationship develops. Arguing that benefits to students, faculty, and institutions outweigh the risks and costs of mentoring, it is written for faculty who want to be better mentors and provides evidence that administrators should value and reward mentoring.

Phases of establishing a mentoring relationship
Every mentoring relationship, no matter at what stage of a student’s progress through college, goes through two or three key phases of development. The most basic step is connection.

Most contemporary students want closer interaction with faculty. They praise a professor who “gets to know everyone in his classes. I was very impressed by how much personal interest he took in his students. He always knew how everyone was doing in the class. He really wanted everyone to do well and went far out of his way to help students that came to him. He cared about his students.” Such appreciation for faculty who “take the time to get to know their students, not just to teach them” is a recurrent theme in the most positive student evaluations.

Connection is encouraged when faculty are available and accessible to talk outside of class. This means holding enough office hours so that conversations can be more than cursory, but it also requires approachability, making students feel invited and welcome when they do come. Students appreciated one professor for holding occasional office hours in a local coffee house on Saturday mornings, for, as one said, “To meet outside [the academic building] lent those meetings more of an aspect of collaboration and discussion, instead of something official or dictated.” Students interpret such faculty efforts as evidence that faculty care about them as people, not just as students. On faculty evaluation forms, students often list “accessibility” or “availability” as a criterion for faculty effectiveness.

Sometimes the Tenure and Promotion Committee has worried that this may signify that the professor encourages dependence or “coddles” students. But understood in context, such student emphasis on faculty accessibility is a corollary to students’ academic engagement and is clearly a sign they are hungry to interact with faculty, eager to know them and be known by them, to establish a connection—a relationship that can open the way to mentoring.
Read more... 

Source: Faculty Focus

Google says machine learning is the future. So I tried it myself | The Guardian

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Photo: Alex Hern

"If deep learning will be as big as the internet, it’s time for everyone to start looking closely at it." inform Alex Hern, technology reporter for the Guardian. 

Google DeepMind’s artificial intelligence program, AlphaGo, used machine learning to defeat its human opponent, but that is just the beginning. 
Photograph: Ahn Young-joon/AP

The world is quietly being reshaped by machine learning. We no longer need to teach computers how to perform complex tasks like image recognition or text translation: instead, we build systems that let them learn how to do it themselves.

“It’s not magic,” says Greg Corrado, a senior research scientist at Google. “It’s just a tool. But it’s a really important tool.”

The most powerful form of machine learning being used today, called “deep learning”, builds a complex mathematical structure called a neural network based on vast quantities of data. Designed to be analogous to how a human brain works, neural networks themselves were first described in the 1930s. But it’s only in the last three or four years that computers have become powerful enough to use them effectively.

Corrado says he thinks it is as big a change for tech as the internet was. “Before internet technologies, if you worked in computer science, networking was some weird thing that weirdos did. And now everyone, regardless of whether they’re an engineer or a software developer or a product designer or a CEO understands how internet connectivity shapes their product, shapes the market, what they could possibly build.”

He says that same kind of transformation is going to happen with machine learning. “It ends up being something that everybody can do a little of. They don’t have to do the detailed things, but they need to understand ‘well, wait a minute, maybe we could do this if we had data to learn from.’”

Google’s own implementation of the idea, an open-source software suite called TensorFlow, was built from the ground up to be useable by both the researchers at the company attempting to understand the powerful models they create, as well as the engineers who are already taking them, bottling them up, and using them to categorise photos or let people search with their voice.

Machine learning is still a complex beast. Away from simplified playgrounds, there’s not much you can do with neural networks yourself unless you have a strong background in coding. But I wanted to put Conrado’s claims to the test: if machine learning will be something “everybody can do a little of” in the future, how close is it to that today?

One of the nice things about the machine learning community right now is how open it is to sharing ideas and research. When Google made TensorFlow open to anyone to use, it wrote: “By sharing what we believe to be one of the best machine learning toolboxes in the world, we hope to create an open standard for exchanging research ideas and putting machine learning in products”. And it’s not alone in that: every major machine learning implementation is available for free to use and modify, meaning it’s possible to set up a simple machine intelligence with nothing more than a laptop and a web connection.

Which is what I did.

Following the lead of writer and technologist Robin Sloan, I trained a simple neural network on 119mb of Guardian leader columns. It wasn’t easy. Even with a detailed readme, it took me a few hours to set up a computer to the point where it could start learning from the corpus of text. And once it reached that point, I realised I had vastly underrated the amount of time it takes for a machine to learn. After running the training software for 30 minutes, and getting around 1% of the way through, I realised I would need a much faster computer.
Read more...

Source: The Guardian

Genius by numbers: why Hollywood maths movies don't add up | Mathematics | Science | The Guardian

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Photo: Stuart Jeffries

Please take a closer look at this article as below by Stuart Jeffries.
He has been a Guardian subeditor, TV critic, Friday review editor, Paris correspondent and is now a feature writer and columnist for the paper.

Pi in the sky … Dev Patel as Indian mathematician Srinivasa Ramanujan in The Man Who Knew Infinity.
Photograph: Warner Bros

In the Tina Fey sitcom Unbreakable Kimmy Schmidt, wealthy Manhattanite Jacqueline Vorhees wails to her assistant that she can’t afford to get divorced. Even though she’d get $1m for every year of her marriage.

“I spend 100 grand a month. I’ll be broke in 10 years,” she wails. “No, that’s wrong,” counters Kimmy (Ellie Kemper), who scribbles some sums with a marker on Mrs Vorhees’s window. “So $100,000 times 12 months. That’s $1.2m a year. Divide that into $12m, and yes, you’d be broke in 10 years. But if you invest some of it, assuming a 7% rate of return, using the compound interest formula, your money would almost double.”

Kimmy turns round triumphantly: “Mrs Voorhees, I mathed, and you can get divorced!” Mrs Vorhees eyes Kimmy narrowly. “Those are not,” she complains, “erasable markers.” What she doesn’t mention is that math isn’t a verb. Not yet.

Hollywood’s most built mathematician … Russell Crowe in A Beautiful Mind. 
Photograph: Universal Studios

The scene is, among other things, Fey’s satire of the Hollywood cliche of genius squiggling on glass. In A Beautiful Mind (2001), for instance, Russell Crowe, playing troubled maths star John Forbes Nash Jr, writes formulae on his dorm window. This scene is echoed in The Social Network (2010), where Andrew Garfield sets out the equations for Facebook’s business model on a Harvard window while Jesse Eisenberg’s Mark Zuckerberg looks on. In the opening scene of Good Will Hunting (1997), janitor prodigy Matt Damon writes equations on a bathroom mirror. 

Why do so many Hollywood maths whizzes forego paper? Stanford mathematician Keith Devlin explains. “Depicting a mathematician scribbling formulas on a sheet of paper might be more accurate, but it certainly doesn’t convey the image of a person passionately involved in mathematics, as does seeing someone write those formulas in steam on a mirror or in wax on a window, nor is it as cinematographically dramatic.”

Good point. When we watch A Beautiful Mind and look through the window at our Russ, Hollywood’s most built mathematician (counterexamples on postcards, please show your workings), we pass beyond incomprehensible equations and convince ourselves we’re seeing Genius at Work. Even if, as some critics have complained uncharitably, Russ’s pi glyphs, greater-than and less-than symbols and such don’t make sense.

But there’s another way maths movies can confound the Boredom Equation, namely by leaving a black hole where the maths should be. The Man Who Knew Infinity, the new film starring Dev Patel and Jeremy Irons about the great Indian mathematician Srinivasa Ramanujan, is intriguing in this respect. Although we see Ramanujan doing maths, mostly the film is interested in other things – how he falls in love with his wife, the pain of separation when he travels from Madras to study at Cambridge, the racism he suffers in England and, most stirringly, the narrative arc from lowly clerk to globally recognised mathematician.
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Source: The Guardian

10 Great Resources Every Math Content Writer Can Use | A Pass Education Blog

"The math course writer of generations past might have relied only on old textbooks in developing content, but the math course writer of today has so much more available to assist in creating high-quality content." writes Liz Arcand as below.  

Photo: A Pass Education Blog

With millions of resources just a click away, it is easier than ever to familiarize yourself with math education’s current best practices and tools. Here are 10 resources for every math course writer to explore:

1.       Common Core State Standards (CCSS) 

Of course, the Common Core standards are one of the most, if not the most, important go-to resource for any math course writer. Standards can be broken down by grade level or domain. Make sure that you’re familiar with the Standards of Mathematical Practice as well.

2.       Open Education Resources 

While there are many educational search engines available, Open Education Resources is one of the better-stocked and organized sites. Check out their Common Core Hub for a plethora of Common Core–aligned tasks and lesson guides to help inform your content and item writing. They also have a section dedicated solely to the instructional shifts of new standards.

3.       Illustrative Mathematics 

This website not only breaks down the standards, but links tasks and sample problems to their respective mathematical domains and standards. Each task also includes a commentary about what a student must know/do to supply a proficient response, as well as possible student misconceptions—perfect for course writers who want to see exemplars of how the standards can be assessed.

4.       Engage NY 

Modules for math courses from pre-kindergarten through high school are available from the New York State Education Department. Not only do they have student and teacher notes, but they also have newly created assessment tasks for each module. A great resource to see continuity across grade levels and how to integrate the Common Core standards into curriculum.

5.       National Council of Teachers of Mathematics (NCTM) 

NCTM advocated for a universal set of mathematical standards at the national level long before the Common Core standards came along, and has been at the forefront of providing quality math resources and professional development for decades. Although many journals require a subscription to access, there are plenty of free lessons and articles available to search without having a membership.

Read more...

Source: A Pass Education Blog

Achieve3000 Unveils Nonfiction Blended Learning Literacy Solutions | T.H.E. Journal

Sri Ravipati, Web producer for THE Journal and Campus Technology inform, "The New Jersey-based company announced new updates to its blended learning poducts." 

 Achieve3000 Pro National Edition from Achieve3000 on Vimeo.

Achieve3000, a provider of cloud-based solutions that deliver differentiated learning instruction, announced several new and updated literacy solutions. The company is releasing state-specific editions for all of its products. Additionally, they announced new products for numerous programs, a makeover to the Teacher’s Edition homepage, and new tools, assessments and full courses.

Achieve3000 has created more than 65 state-customized editions of its nonfiction blended learning literacy solutions:

• KidBizPro, TeenBizPro and EmpowerPro for English language arts, science and social studies;
• KidBizBoost, TeenBizBoost and EmpowerBoost for Tier II and III response to intervention and special education;
• KidBizAccess, TeenBizAccess and EmpowerAccess for English language learners; and
• KidBizEspañol, TeenBizEspañol, and EmpowerEspañol for Spanish language learners.

Each of the blended learning literacy solutions has assessments, available in both English and Spanish, that measure and monitor students’ reading levels.

In addition, Achieve3000 launched its ELA Test Challenge, courses that prepare students for high-stakes state assessments. The courses help students achieve stamina through practicing with drag-and-drop sequencing, click-to-highlight tasks and multiple-choice questions. The Challenge courses are available through Achieve3000’s mobile apps, both online and offline.
Read more... 

Source: T.H.E. Journal

Supporting Learning Outcomes 4-pack | Magna Publications

"Understand how to support the knowledge and skills determined by your course’s learning outcomes. These programs will help you structure and plan classroom activates to maximize student engagement, increase student participation, and ultimately deepen learning." summarizes Magna Publications.

Photo: Magna Publications

The Supporting Learning Outcomes 4-pack is a series of our acclaimed 20-Minute Mentors. This collection was designed to provide you a  multidimensional approach to utilizing and sustaining learning outcomes in your courses.

Plus, each program is only 20 minutes long!

In the Supporting Learning Outcomes 4-pack you’ll learn tips and techniques grounded in theory and tested in face-to-face and online classrooms.

From suggestions for changing your first class procedures to preemptive feedback, all the suggestions you’ll learn are proven and practical. 

The programs cover key issues involved with helping students achieve learning outcomes—and give you the specifics you need to make effective change, such as:

• Exams – Learn how changing your exam previews and reviews can put the focus back on learning.
• Feedback – Explore four specific practices to get students more involved.
• Discussion – Find out how to reinforce the classroom behavior you want to see.
• Responsibility – Discover how changing your personal style can make students behave more responsibly.

Each presentation delivers insightful information you can implement immediately.

Learning outcomes are so central to success in higher education; you need to sustain them in multiple ways. Get the tools you need in the Supporting Learning Outcomes 4-pack.

Higher education experts Maryellen Weimer, Ph.D., Jean Mandernach, Ph.D., Jay Howard, and Christy Price, Ed.D. explore solutions to the following key questions:

1. How Can I Use Discussion to Facilitate Learning?
   In this program, you will learn how to structure and plan classroom discussions to maximize student engagement, student participation, and learning.
2. How Can I Get Students to Take Responsibility for Their Own Learning?
   This presentation will show you how clear communication and consistent application of standards can help students become more effective and engaged learners.
3. How Can I Enhance the Impact of Feedback in Online Classes?
   Discover how dynamic feedback strategies such as feedforward, expanded multimedia use, one-to-many presentation, and peer-to-peer delivery can change student behavior.
4. How Can I Make My Exams More about Learning, Less about Grades?
   Learn how you can transform exams into enhanced opportunities for student learning with practical solutions to the three core problems with exams today.

Taken altogether, these programs provide you with a comprehensive approach to fulfilling your most important job requirement—helping students learn. 

This series of Magna 20-Minute Mentors is perfect for faculty teaching online and offline, at public and private institutions, and at all stages of their careers. It will be particularly helpful for new instructors, providing them with “instant experience.”

Buy your video today. 

Source: Magna Publications