Welcome to Q-bits!

This blog channel is your gateway to Q-bits, online modules designed by our faculty to support students with quantitative skills and reasoning across the disciplines.  In the posts below, you can find information and links to each Q-bit that is hosted in your campuses learning management system (LMS) for easy access.

⇒ Students, please leave us a comment about your experience using any of the Q-bits in the posts below.  We invite your suggestions on how to improve current modules, or what other topics might be useful to you!

⇒ Faculty, for more information about using Q-bits with your students, we invite you to watch this short video: Q-bits Tutorial.

Q-bits available in Fall 2017:

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QLAB update: piloting Q-bits with students (Fall ’17)

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Prof. Ming An (Vassar College), lead author of the 'Choosing a Graph Type' Q-bit
Prof. Ming An (Vassar College), lead author of the ‘Choosing a Graph Type‘ Q-bit

starQLAB Webinar 11/15: 
click here to jo
in the discussion

 

This summer and fall, teams of faculty and technologists collaborated intensively to launch QLAB, a shared framework for curating, implementing and assessing online instructional modules for quantitative skills (QS) and reasoning for just-in-time review and skill-building across disciplines.  The goal of the QLAB project is to assist faculty teaching quantitative subjects who find they need methods to support students with gaps in preparation. The strategy draws on a body of research in higher education and experience at our institutions showing that online modules can be a beneficial component of an overall QS support program.

The individual modules, known as Qbits, review quantitative topics and demonstrate the topic’s applications in different disciplinary contexts.  For example, a module might review logarithms and then consider the application to decibels and sound perception in psychology, the Richter scale in geology, the concept of pH in chemistry, etc. In Fall 2017, Qbits are being implemented through a combination of videos and quizzing, and consist of an initial knowledge check, short videos to review specific quantitative skills, structured application problems that give students practice applying the quantitative skill in disciplinary contexts, and a final knowledge check.

Q-bits tested in Fall 2017:

project.
QLAB session
June 2017

Developing online resources that can be used in multiple contexts to help students strengthen their quantitative skills serves two purposes. First, by demonstrating the relevance of specific QS in various disciplinary contexts, students learn to view quantitative skills as fundamental and transferable skills that they can draw on in many areas of their liberal arts experience. Second, the consortial effort allows us to collect meaningful data about the effectiveness of the various modules for a greater number of students in a wider variety of contexts.  Using what we learn in this pilot, we plan to expand the collection of useful modules.

Aims of the pilot include:

  • Developing a collaborative framework for design, implement and assessment of online modules for QS/QR instruction and review at residential liberal arts institutions.
  • Crafting an initial set of instructional modules on high-priority QS topics, drawing on high quality instructional content, developed in partnership with Yale ONEXYS and others.  
  • Assessing module effectiveness as refreshers for tutoring and as just-in-time instruction embedded in coursework.
  • Gathering data to evaluate the impact of modules on student learning and confidence in each phase of the project and beyond.

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Q-bit: Logarithms

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LACOL_MKAlgebra:
Logarithms
Module Purpose: This module guides students on key concepts for working with logarithms in different disciplinary contexts.

Module Authors: Melissa Eblen-Zayas, Carleton College, Jim Rolf and Yale ONEXYS, with additional problems contributed by LACOL faculty, instructors and QS/QR tutors.

Notes on Strategy: 

  1. Watch the instructional videos to review some basic characteristics of logs and different ways that they can be used.
  2. Gain practice in applying your knowledge through problem solving.

Application Problems:

  • Perception of Sound (Psychology)
  • Acidity of Chemical Solutions (Chemistry)
  • Radioactive Materials – Rate of Decomposition (Chemistry, Physics)
  • Earthquakes and the Richter scale (Geology)
  • Binary Representation of Data (Computer Science)
  • Binary Search (Computer Science)
  • Doubling the Value of an Investment (Economics)
STUDENTS: Access the ‘Logarithms‘ Q-bit in your LMS! 

Carleton College: contact the Academic Technology team in ITS for access in Moodle.

Haverford College: https://moodle.haverford.edu/course/view.php?id=678

Williams College: contact the OIT team for access in GLOW.

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Q-bit: Linear Functions

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LACOL_MKAlgebra:
Linear Functions
Module Purpose: This module guides students on key concepts for working with linear functions in different disciplinary contexts.

Module Authors: Adam Honig, Amherst College, Jim Rolf and Yale ONEXYS, with additional problems contributed by LACOL faculty, instructors and QS/QR tutors.

Notes on Strategy: 

  1. Watch the instructional videos to review some basic characteristics of linear functions and different ways that they can be used.
  2. Gain practice in applying your knowledge through problem solving.

Application Problems:

  • The Keeling Curve
  • Moving Objects
  • Linear Functions in the Supply and Demand Model: Numerical Examples
  • Linear Functions in the Supply and Demand Model: Slopes and Intercepts
  • The Consumption Function
STUDENTS: Access the ‘Linear Functions‘ Q-bit in your LMS! 

Carleton College: contact the Academic Technology team in ITS for access in Moodle.

Haverford College: https://moodle.haverford.edu/course/view.php?id=646

Williams College: contact the OIT team for access in GLOW.

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Q-bit: Choosing a Graph Type to Visualize Data

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LACOL_MKGraphing:
Choosing a Graph Type to Visualize Data
Module Purpose: This module guides students on steps to think about the variables they’re exploring and select the best graph type to visualize them.

Module Authors: Ming-Wen An, Vassar College; Albert Y. Kim, Amherst College, with additional problems contributed by LACOL faculty, instructors and QS/QR tutors.

Notes on Strategy: 

  1. Watch the instructional videos and be wowed by the power of data visualization.
  2. Understand the importance of identifying the types of variables in your research question.
  3. Gain practice in selecting the graph type that is best suited to visualize your data.

Application Problems:

  • Biology: Personal Genomics – Quantifying Genetic Variation among Individuals
  • Economics: Discovering the Law of Supply and Demand
STUDENTS: Access the ‘Choosing a Graph Type’ Q-bit in your LMS! 

Carleton College: contact the Academic Technology team in ITS for access in Moodle.

Haverford College: https://moodle.haverford.edu/course/index.php?categoryid=44

Vassar College: http://moodle.vassar.edu/course/view.php?id=11931

Williams College: contact the OIT team for access in GLOW.

We welcome your feedback!! Please leave a comment below to let us know how this q-bit was helpful to you.  What would make it more helpful?  Do you have suggestions for other q-bits? 

[COMMENTS CURRENTLY CLOSED]

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Nov 15: QLAB Webinar – Update on Q-bits Testing in Fall ’17 Pilot (+ What’s Next?)

M. Eblen-Zayas
M. Eblen-Zayas

Event: Webinar – Update on Q-bits Testing in the Fall 2017 Pilot / What’s Next?
Location: ZOOM (details below)
Date: Wednesday, November 15
Time:
12:00 noon – 1PM Eastern
Presenter: Prof. Melissa Eblen-Zayas & QLAB Core Team

 

You are invited to join a webinar update and discussion about QLAB, the multi-campus collaboration to develop a shared framework for curating, implementing and assessing online instructional modules to assist students with quantitative skills and reasoning across disciplines.

NB: A recording of the webinar will be shared for those who cannot join in person.

Read more about the pilot: http://lacol.net/qbits-pilot

Webinar Agenda: The goal of this session is to bring those who are interested up-to-speed with where the QLAB project stands, what we have learned so far, and what our next steps might be. We will be looking for input on approaches to revising the existing Q-bits, choosing topics for the next several Q-bits to be developed, and lowering barriers to contributing to the project.

    • Status of the Q-bit project — goals, what makes this project different, overview of what we have done
    • Lessons learned so far
    • Seeking input on some next steps

 

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Webinar: Using Q-bits with Students (Fall 2017)

Curious about Q-bits? Watch the webinar (30 min):


M. Eblen-Zayas
M. Eblen-Zayas

This video presents a half-hour webinar training with Prof. Melissa Eblen-Zayas of Carleton College and members of the QLAB Project core team. Melissa provides an overview of Q-bits and answers questions about testing in the upcoming term.   

Related Resources:

Please feel free to forward this post to colleagues who may be interested in Q-bits! The webinar is an great way preview a Q-bit and learn more about our multi-campus collaboration to develop and test ways these modules may help to support students with their quantitative work in different disciplinary contexts.  

Q-bit Training Outline:

  • What are Q-bits?  (a brief tour)
  • Our pilot study – research goals
  • Options and steps for testing Q-bits with your students
  • Key dates 
  • Resources for Q-bit Testers
  • Q&A

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A new LACOL collaboration will develop Qbits to support students with quantitative skills and reasoning

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M. Eblen-Zayas
Above: Physicist M. Eblen-Zayas, Carleton College

Top: Mathematician M. Stoicu, Williams College at the 2017 QS Hackathon

To assist our students with readiness for their quantitative work across the curriculum, LACOL’s Quantitative Skills working group is launching a multi-campus initiative, nicknamed QLAB. Through this collaboration, faculty and technologists are teaming up to build a shared framework for curating, implementing and assessing instructional modules for quantitative skills (QS) and quantitative reasoning (QR). The strategy draws on a body of research in higher education and experience at our institutions showing that online modules can be a beneficial component of an overall QS/QR support program.

According to project co-lead Melissa Eblen-Zayas, Associate Professor of Physics and Director of the Perlman Center for Learning and Teaching, Carleton College:

The QLAB project addresses a challenge that many of us are facing — we want all students to be successful regardless of their high school math preparation. Currently, each faculty member teaching a course that makes use of basic quantitative skills (QS) must find ways to support students with weak QS preparation. Rather than having faculty members develop all of their own support resources, this project will develop shared online modules – Qbits – that can be deployed for just-in-time review and skill-building in a number of disciplines.

Developing online resources that can be used in multiple contexts to help students strengthen their quantitative skills serves two purposes. First, by showing how these skills are relevant in various disciplinary contexts, students learn to view quantitative skills as fundamental and transferable skills that they can draw on in many areas of their liberal arts experience. Second, as a consortial effort, we will have more students using these modules in a variety of contexts so that we can collect meaningful data about the effectiveness of the various modules, and improve them accordingly.

Groundwork for the project was laid during the QS Framework Hack-a-thon held at Carleton College in January 2017.  At that workshop, faculty and technologists created module prototypes and explored research questions based on the common needs and challenges the partner schools experience as small, residential liberal arts institutions.
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LACOL Hack-a-thon Toward a Collaborative Quantitative Skills Support Framework

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See also: QLAB project launch http://lacol.net/qlab-launch

This January, LACOL’s Quantitative Skills working group held a 3­-day intensive workshop (also known as a hack­-a­-thon) to explore a shared framework for review of online modules designed to strengthen students’ quantitative skills (QS) and quantitative reasoning (QR). The face-to-face event was designed by a core team of faculty and technologists from the QS group.  The workshop was hosted at Carleton College, with support from the Office of the President, Perlman Center for Learning and Teaching, and Office of Academic Technology.

Click for the Slideshow
Click for the Slideshow

Goals for the LACOL QS hack-a-thon:

  1. Identify aspects of existing QS/QR curricula, frameworks, and methods to be adapted as an online module/program by participating colleges. The goal for the collaboration is to enhance, not replace, local offerings.
  2. Plan for participating campuses to pilot one of the frameworks and agree to a process for assessment and sharing results among campuses.
  3. Document workshop outcomes and recommendations to share with colleagues across the liberal arts.

Location: Carleton College

Dates: Jan 9-11, 2017 (live blogging)

Workshop Outline: click here

Special Guest: Jim Rolf, Shizuo Kakutani Lecturer in Mathematics at Yale University; lead for Yale Online Experiences for Yale Scholars (ONEXYS)

Workshop Participants: list

Background:

Throughout the year, the QS working group has been exploring ideas for a collaborative framework to curate or build online tools and resources – including metadata on related pedagogical practices – to support students with QS/QR. Earlier this year, QS group members contributed to a joint exercise informally titled “What do we mean by quantitative skills?” to generate a shared list of key skills across the quantitative disciplines that students will need to have or acquire early in their academic careers. This common skills list provides input into strategies for helping students identify and close gaps.
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Project Summary: QLAB / Q-bits Framework for Quantitative Skills Modules

To assist our students with readiness for their quantitative work across the curriculum, and to investigate the role that online resources may play in this, the Liberal Arts Consortium for Online Learning (LACOL) has kicked off a multi-campus development and educational research initiative, nicknamed QLAB. The QLAB project provides a framework for creating a series of modules called Q-bits. Each online Q-bit module focuses on a particular quantitative skill or concepts and provides instructional and review content that is “wrapped” by pre/post knowledge and confidence checks, contextual guides, and applications problems in several disciplines.

In developing Q-bits, the instructional content is hand-selected by our faculty in order to achieve of an appropriate scope and level for students. In many cases, faculty are able to draw on existing high-quality materials, especially on a set of polished instructional videos shared by our collaborators at Yale University through their ONEXYS program. In some cases, faculty are adding custom introductory or instructional components to provide cues for students so they see how each Q-bit relates to their studies in different disciplinary contexts.

In testing Q-bits, LACOL faculty and instructors are well positioned to assess the effectiveness of the online modules in the context of in-class assignments, as refreshers alongside a class, or in the context of mentoring by academic support staff or peer tutors.

Project Leads:

  • Melissa Eblen-Zayas, Assoc. Professor Physics, Carleton College
  • Adam Honig, Professor of Economics, Amherst College
  • Laura Muller, Director Peer Instruction, Williams College
  • Janet Russell, Director Academic Technology, Carleton College

Related Posts:

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