We examined predictors of Calculus II final grades within a sample of 84 college students enrolled in a hybrid course through WEPS. Predictors included “typical” psychological correlates, including math confidence, math anxiety, spatial skills and numerosity ability, as well as clickstream data from the students’ activity in the online course. Results showed the clickstream data were the best predictors of course performance, in that students who spent more time grading other students’ assignments, and students who took fewer quiz attempts, did better in the course. Math confidence and then math anxiety were the next best predictors, in that students with higher confidence and lower math anxiety performed better in the course. We will discuss how results might be dependent on the particular content of this course, and how we might use easy to collect psychological variables along with clickstream data to better understand, and potentially predict, course performance in online courses.
Investigating learning strategies in a dispositional learning analytics conte...Bart Rienties
This study aims to contribute to recent developments in empirical studies on students’ learning strategies, whereby the use of trace data is combined with self-report data to distinguish profiles of learning strategy use [3, 4, 5]. We do so in the context of an application of dispositional learning analytics in a large introductory course mathematics and statistics, based on blended learning. Building on our previous work which showed marked differences in how students used worked examples as a learning strategy [7, 11], this study compares different profiles of learning strategies with learning approaches, learning outcomes, and learning dispositions. One of our key findings is that deep learners were less dependent on worked examples as a resource for learning, and that students who only sporadically used worked examples achieved higher test scores.
Real-time Assessment: A Guide for Emergency Remote TeachingFitri Mohamad
This is a set of materials from a webinar held for Universiti Malaysia Sarawak's lecturers (UNIMAS), to guide the transition from f2f teaching to emergency remote teaching - specifically on conducting Real-time Assessments.
Learn about SBAC's definition for formative assessment and tech tools that can be used to gather student data, give feedback, and capture student thinking.
Investigating learning strategies in a dispositional learning analytics conte...Bart Rienties
This study aims to contribute to recent developments in empirical studies on students’ learning strategies, whereby the use of trace data is combined with self-report data to distinguish profiles of learning strategy use [3, 4, 5]. We do so in the context of an application of dispositional learning analytics in a large introductory course mathematics and statistics, based on blended learning. Building on our previous work which showed marked differences in how students used worked examples as a learning strategy [7, 11], this study compares different profiles of learning strategies with learning approaches, learning outcomes, and learning dispositions. One of our key findings is that deep learners were less dependent on worked examples as a resource for learning, and that students who only sporadically used worked examples achieved higher test scores.
Real-time Assessment: A Guide for Emergency Remote TeachingFitri Mohamad
This is a set of materials from a webinar held for Universiti Malaysia Sarawak's lecturers (UNIMAS), to guide the transition from f2f teaching to emergency remote teaching - specifically on conducting Real-time Assessments.
Learn about SBAC's definition for formative assessment and tech tools that can be used to gather student data, give feedback, and capture student thinking.
Cengage Learning Webinar, Psychology, Teaching the Psychology of Adjustment a...Cengage Learning
The old adage "Try, try again" suggesting persistence leads to success turns out to be true, according to recent research. In this April 16, 2013 session discussed ideas that will help your students become better learners and more successful in endeavors beyond the classroom.
Ten years ago there were no educational products available for K-12 Math that were truly adaptive. Now just about everyone claims to be adaptive in some way. But what does it mean to be “adaptive”? How do these products work? And how do you evaluate which best fits your needs?
In this presentation, Nigel Green, Vice President of User Experience at DreamBox Learning, discusses the evolving definition of adaptive learning and it's application in varying technologies and approaches, including: how different student actions and behaviors can inform an adaptive engine, how adaptive learning programs can be integrated into your blended learning models, and some of the possible futures of adaptive learning.
NC3ADL Session: Leveraging Digital Media to Personalize the Path to College Readiness (Presentation provided by Angie Smajstrla)
This session will share examples of how educators are leveraging adaptable, affordable online resources from the non-profit NROC project to support teaching and learning innovations. We will look especially at how Developmental Math - An Open Program is being used both in and out of the classroom to personalize learning experiences for students striving to accelerate the path to college readiness. NROC resources are available to all NC Community Colleges through a partnership with NCCCS.
Presenter(s): Angie Smajstrla (The NROC Project); Wanda Barker (NCCCS); Kathy Davis (NCCCS); Jonathon Sweetin (NCCCS)
Empowering Pre-Service & New Math Teachers to Use the Common Core Practice St...DreamBox Learning
How prepared are the K-12 teachers of tomorrow to inspire the next generation of young mathematicians? In this webinar for the edWeb.net Adaptive Math Learning community, attendees learned how essential it is for pre-service teachers to learn, develop, and model the Standards for Mathematical Practice to improve learning for their future students. Ben Braun, Associate Professor of Mathematics at the University of Kentucky, and Tim Hudson, Senior Director of Curriculum Design at DreamBox Learning, discussed ways to ensure that pre-service teachers start their careers understanding how mathematical proficiency requires more than simply content knowledge. Tim and Ben shared ideas for K-12 school leaders and mentor teachers who are responsible for new teacher induction, as well as, implications for college and university faculty teaching both math methods and content courses. They also discussed potential disconnects between pre-service content and methods courses and also eventual in-service expectations, while providing examples of math problems to engage pre-service and new teachers. View the webinar to better understand how to use the Standards for Mathematical Practice.
This paper presents a proactive anonymous feedback based adaptive teaching for enhancing student learning for engineering courses. In conventional university teaching, typically, students come to the class and instructors lecture the material, assign home assignments, take exams, etc. After grading assignments or exams, the instructor provides feedback to students. Most of the time, students are reluctant to ask questions or ask instructor to revisit the topic which was already covered. However, there is no immediate anonymous feedback mechanism for each topic or class to notify the instructor about topics which are not clear to students. There are advantages that enhance students’ learning experience by using a proactive anonymous feedback approach in teaching, learning and assessment. In this paper, we present the
immediate impacts of proactive anonymous feedback based adaptive teaching on student learning and assessment. Furthermore, anonymous online based feedback mechanism provides faster feedback than conventional mechanism (where students wait until the first exam or so). Immediate feedback for each topic discussed in the class streamlines the process of reporting and the provision of active studying. The results
show that students get better grade and instructors get better student evaluation score since the anonymous feedback provides a mechanism for students to ask questions anonymously and the instructors get an opportunity to answer the questions or concerns in a timely manner. We implemented the proactive anonymous feedback approach in many courses in different semesters and observed similar results. However, as an example, we present one course and instructor to illustrate the effectiveness of the proposed approach.
Empowering Teacher Agency: How Data-Driven PD Models are Improving K-5 Math A...DreamBox Learning
Just as teachers struggle to find time and resources that support differentiation and personalization for every student in math class, administrators struggle to provide differentiated professional learning options for teachers that are relevant to their classroom and easily accessible.
To improve elementary student achievement in math, district administrators must explore innovative approaches to professional development that improve teachers’ understanding of mathematics concepts. In this webinar, Dr. Tim Hudson, VP of Learning at DreamBox Learning shared how to:
Adopt a new model of online professional learning that empowers teachers to use real-time student data to access “just in time” professional learning resources that are specific to their students and classrooms.
Implement best practices for driving teacher agency in PD, such as empowering teachers to use data to choose PD topics that address the real challenges in their classrooms.
Ensure equitable learning outcomes for all students in mathematics by also ensuring equitable professional learning outcomes for all mathematics teachers.
EPSS for Faculty Development (In-Progress Project)Saul Carliner
In this project, a team comprised of members from university and a Cegep are developing an alternate approach to professional development: an electronic performance support system (EpSS) that provides teaching support online and consists of (a) generalized and discipline-specific research-based guidance for their most significant challenges as identified by a needs assessment; (b) teaching cases that illustrate practical applications in the classroom and (c) other approaches to engage faculty with this system. This session, by the research team describes the system and summarizes the first topics covered.
2nd That Emotion: Support for the Affective DomainFred Feldon
Los Angeles Valley College AB 705 Math Workshop, May 17, 2019. Design principles for high-challenge, high-support curricula and pedagogy includes intentional support for students' affective needs. The non-cognitive domain plays an undeniable role in reducing students' fears and increasing students' willingness to engage with challenging tasks.
Cengage Learning Webinar, Psychology, Teaching the Psychology of Adjustment a...Cengage Learning
The old adage "Try, try again" suggesting persistence leads to success turns out to be true, according to recent research. In this April 16, 2013 session discussed ideas that will help your students become better learners and more successful in endeavors beyond the classroom.
Ten years ago there were no educational products available for K-12 Math that were truly adaptive. Now just about everyone claims to be adaptive in some way. But what does it mean to be “adaptive”? How do these products work? And how do you evaluate which best fits your needs?
In this presentation, Nigel Green, Vice President of User Experience at DreamBox Learning, discusses the evolving definition of adaptive learning and it's application in varying technologies and approaches, including: how different student actions and behaviors can inform an adaptive engine, how adaptive learning programs can be integrated into your blended learning models, and some of the possible futures of adaptive learning.
NC3ADL Session: Leveraging Digital Media to Personalize the Path to College Readiness (Presentation provided by Angie Smajstrla)
This session will share examples of how educators are leveraging adaptable, affordable online resources from the non-profit NROC project to support teaching and learning innovations. We will look especially at how Developmental Math - An Open Program is being used both in and out of the classroom to personalize learning experiences for students striving to accelerate the path to college readiness. NROC resources are available to all NC Community Colleges through a partnership with NCCCS.
Presenter(s): Angie Smajstrla (The NROC Project); Wanda Barker (NCCCS); Kathy Davis (NCCCS); Jonathon Sweetin (NCCCS)
Empowering Pre-Service & New Math Teachers to Use the Common Core Practice St...DreamBox Learning
How prepared are the K-12 teachers of tomorrow to inspire the next generation of young mathematicians? In this webinar for the edWeb.net Adaptive Math Learning community, attendees learned how essential it is for pre-service teachers to learn, develop, and model the Standards for Mathematical Practice to improve learning for their future students. Ben Braun, Associate Professor of Mathematics at the University of Kentucky, and Tim Hudson, Senior Director of Curriculum Design at DreamBox Learning, discussed ways to ensure that pre-service teachers start their careers understanding how mathematical proficiency requires more than simply content knowledge. Tim and Ben shared ideas for K-12 school leaders and mentor teachers who are responsible for new teacher induction, as well as, implications for college and university faculty teaching both math methods and content courses. They also discussed potential disconnects between pre-service content and methods courses and also eventual in-service expectations, while providing examples of math problems to engage pre-service and new teachers. View the webinar to better understand how to use the Standards for Mathematical Practice.
This paper presents a proactive anonymous feedback based adaptive teaching for enhancing student learning for engineering courses. In conventional university teaching, typically, students come to the class and instructors lecture the material, assign home assignments, take exams, etc. After grading assignments or exams, the instructor provides feedback to students. Most of the time, students are reluctant to ask questions or ask instructor to revisit the topic which was already covered. However, there is no immediate anonymous feedback mechanism for each topic or class to notify the instructor about topics which are not clear to students. There are advantages that enhance students’ learning experience by using a proactive anonymous feedback approach in teaching, learning and assessment. In this paper, we present the
immediate impacts of proactive anonymous feedback based adaptive teaching on student learning and assessment. Furthermore, anonymous online based feedback mechanism provides faster feedback than conventional mechanism (where students wait until the first exam or so). Immediate feedback for each topic discussed in the class streamlines the process of reporting and the provision of active studying. The results
show that students get better grade and instructors get better student evaluation score since the anonymous feedback provides a mechanism for students to ask questions anonymously and the instructors get an opportunity to answer the questions or concerns in a timely manner. We implemented the proactive anonymous feedback approach in many courses in different semesters and observed similar results. However, as an example, we present one course and instructor to illustrate the effectiveness of the proposed approach.
Empowering Teacher Agency: How Data-Driven PD Models are Improving K-5 Math A...DreamBox Learning
Just as teachers struggle to find time and resources that support differentiation and personalization for every student in math class, administrators struggle to provide differentiated professional learning options for teachers that are relevant to their classroom and easily accessible.
To improve elementary student achievement in math, district administrators must explore innovative approaches to professional development that improve teachers’ understanding of mathematics concepts. In this webinar, Dr. Tim Hudson, VP of Learning at DreamBox Learning shared how to:
Adopt a new model of online professional learning that empowers teachers to use real-time student data to access “just in time” professional learning resources that are specific to their students and classrooms.
Implement best practices for driving teacher agency in PD, such as empowering teachers to use data to choose PD topics that address the real challenges in their classrooms.
Ensure equitable learning outcomes for all students in mathematics by also ensuring equitable professional learning outcomes for all mathematics teachers.
EPSS for Faculty Development (In-Progress Project)Saul Carliner
In this project, a team comprised of members from university and a Cegep are developing an alternate approach to professional development: an electronic performance support system (EpSS) that provides teaching support online and consists of (a) generalized and discipline-specific research-based guidance for their most significant challenges as identified by a needs assessment; (b) teaching cases that illustrate practical applications in the classroom and (c) other approaches to engage faculty with this system. This session, by the research team describes the system and summarizes the first topics covered.
2nd That Emotion: Support for the Affective DomainFred Feldon
Los Angeles Valley College AB 705 Math Workshop, May 17, 2019. Design principles for high-challenge, high-support curricula and pedagogy includes intentional support for students' affective needs. The non-cognitive domain plays an undeniable role in reducing students' fears and increasing students' willingness to engage with challenging tasks.
You can't spell CMS without content - Simon Wong CS Forum 2016Simon Wong
If you're going to invest in a new CMS, make sure you invest in the content for it too. Here's how to get everyone on board, and to get content planned, created, and delivered for a successful go-live and beyond. I realise this doesn't have the context of a verbal presentation, so please contact me if you'd like more details.
The Equity Scholarship Provision in Australian Universities: Insights and Directions forum was held at the University of Canberra on Wednesday 11 February 2015. Against the backdrop of the higher education deregulation debate, the NCSEHE undertook to deepen understandings and contribute in a meaningful way to the national discourse on equity scholarships.
From newspapers to newsbrands: challenging the mythsNewsworks
Newsworks looks at some common misconceptions newsbrands face, including 'young people don't read newsbrands' and 'social media is killing newsbrands'.
Piotr Wilam - Product Development Days - Raise the bar highInnovation Nest VC
Piotr Wilam's talk at PDD 2015 in Krakow. Piotr Talks about his experience with product design from Investor POV. Check out the presentation for better overview.
How to run system administrator recruitment process? By creating platform based on open source parts in just 2 nights! I gave this talk in Poland / Kraków OWASP chapter meeting on 17th Octomber 2013 at our local Google for Entrepreneurs site. It's focused on security and also shows how to create recruitment process in CTF / challenge way.
This story covers mostly security details of this whole platform. There's great chance, that I will give another talk about this system but this time focusing on technical details. Stay tuned ;)
The 100 acre resort is nestled in the unspoiled sylvan setting of the Nature . A short drive from Mumbai and Pune brings you to this sanctuary for the body, mind and spirit. Located amidst the breathtaking landscape of the Western Ghats, and a range of recreational options. The property also offers an inspiring backdrop for exclusive corporates, schools, collages and FIT group social gatherings.
Resort organises classes for local cuisine cooking as well as dance and pottery studios. Explore the vast surroundings of the estate on nature walks and treks though the unspoilt forest, or go mountain biking across the stunning landscape.It is a land of picturesque picnic spots, advertisement, movie shooting also popular for summer-winter camps and weekend getaway for many families Surrounding mumbai and pune.
Highlights
Exclusive setting within the serene landscape of the Western Ghats
Personalized service available
20-minute speed boat drive from Panshet/Warsgaon boating to Lavasa located nearby
Experience the thrill of dence forest with natural water fall and wild life
A range of recreational activities and excursions offered
More Details,
www.lakeweekendresort.in
Methods of collecting data
Survey, methods and type, response rate, variable language
Hands on: Graphical techniques II, SPSS
Questionnaire design
Tips on writing a research paper
Individual project: article critique
Cognitive, personality and behavioural predictors of academic success in a la...Blackboard APAC
In recent years there has been growing interest in the use of e-learning tools that are able to adapt to suit the ability levels, needs, or preferences of individual learners. In this project we aim to test the utility of an adaptive e-learning study tool within the context of a large undergraduate Psychology course (approximately 700 students). The study tool and a number of associated summative tests are hosted on the course’s Blackboard Learning Management System. Pilot data indicates that students that use the tool perform significantly better on the summative tests compared to non-users (t[683] = 4.35, p <0.001). We examine the relationship in the context of 1) learning analytics data that can be obtained via Blackboard, and 2) a number of known psychological predictors of academic success.
Delivered at Innovate and Educate: Teaching and Learning Conference by Blackboard. 24 -27 August 2015 in Adelaide, Australia.
Presentation at the HEA-funded workshop 'Making undergraduate social science count: engaging sociology and criminology students in quantitative research methods'.
This workshop aimed to encourage pedagogical reflection and debate on the teaching of quantitative methods to sociology/criminology undergraduates and provide delegates with opportunities for the sharing of best practice in this area. The event included dissemination of the outputs of two recent HEA-funded projects on teaching research methods in the social sciences. Delegates were also introduced to some new and existing quantitative datasets and resources and explore the potential for integrating these across the undergraduate curriculum.
This presentation is part of a related blog post that provides an overview of the event: http://bit.ly/1iBrVMR
For further details of the HEA's work on teaching research methods in the Social Sciences, please see: http://bit.ly/15go0mh
The power of learning analytics to unpack learning and teaching: a critical p...Bart Rienties
Across the globe many educational institutions are collecting vast amounts of small and big data about students and their learning behaviour, such as their class attendance, online activities, or assessment scores. As a result, the emerging field of Learning Analytics (LA) is exploring how data can be used to empower teachers and institutions to effectively support learners. In the recent Innovative Pedagogy Report Ferguson et al. (2017) encourage researchers and practitioners to move towards a new form of learning analytics called student-led learning analytics, which enable learners to specify their own goals and ambitions. They also support learners to reach these goals. This is particularly helpful for individuals who have little time to spare for study. In this ESRC session, based upon 6 years of experience with LA data and large-scale implementations amongst 450000+ students at a range of context, I will use an interactive format to discuss and debate three major questions: 1) To what extent is learning analytics the new holy grail of learning and teaching? 2) How can instructional design be optimised using the principles of learning analytics?; 3) With the introduction of student-led analytics, to what extent can learning analytics promote ‘personalisation’ or ‘generalisation’ for diverse populations of students?
Practical techniques for special educators to use in their math classrooms. The most recent developments in math assessments from SBAC will also be shared. (Presented by Dr. Julie Jones, USC Upstate. - uploaded here with permission from Dr. Jones).
With the unbelievable success of my previous survey research lecture, I felt it only right to keep going with that theme. This presentaiton is a copy of a guest lecture I recently did for the Clinical Epidemiology course here at The University of Iowa. The slides first talk about some fundamentals of psychmetric measurement like reliability and validity, and then get practical by discussing 5 simple strategies for creating successful survey instruments. Like, favorite, share, comment, enjoy!
Personalized learning is one of the main ideals that many educational institutions strive to provide for their students. Learning analytics with its promise to help understand and optimize learning and the environments in which learning happens has eagerly been received in this context. Existing research in learning analytics has dedicated much attention to studies that aimed at identifying factors predicting different learning outcomes based on learners’ interaction with technology. Existing research indicates that learning is a dynamic process that is driven by feedback loops. If those feedback loops are not accounted for comprehensively, opportunities for creating personalized learning experiences are limited. However, there is the dearth of research that focuses on understanding how learning unfolds over a certain period of time under different conditions. This talk will describe different factors that influence students’ feedback loops and decision making. The talk will also discuss insights gained in several case studies that looked at dynamic models of learning.
Videos are used extensively in cyber learning. Analyzing video data and using interactive videos in cyberlearning are emerging areas in learning technologies and big data analytics.
Novel video analytics tools can transform traditional (linear) videos into interactive learning objects; therefore improve the classroom interactions and students’ engagements. Data from cybersecurity program at University of Maryland show that students’ engagements improved six times after a video analytics tool (inVideo) was introduced.
The presenter will discuss the latest development of inVideo, a video analytics tool that is able to analyze video content automatically in both language and frames. In addition, the presenter will discuss correlations between low accuracy in automatic transcripts with early recording methods that produce huge ambient noises and echo. The research finding is helpful for curricula developments in cyberlearning so that newly produced videos can be indexed, searched and annotated.
Using the video data analytics technologies, long videos can be easily “cropped” and annotated so that learners can easily focus on important concepts during their study. Though tested in cybersecurity education, this technology can be easily applied to math and other STEM subjects in cyberlearning setting.
In this presentation we describe computer aided assessment methods used in online Calculus courses and the data they produce. The online learning environment collects also a lot of timestamped data about every action a student makes. Furthermore, information about students’ learning styles, motivation and perception of self efficacy is collected by questionnaires.
Mika Seppälä started intensive work at the University of Helsinki to develop online materials and tools for learning mathematics since 2001. He worked also as a professor at the Florida State University where he utilized these methods in Calculus teaching. The open online course “Single Variable Calculus” was held in Helsinki 2004. This seminal work evolved into a complete online English Calculus curriculum starting from the Fall 2013 and soon recognized as an alternative route for taking traditional university Calculus courses in Helsinki.
Automatic assessment systems of mathematical competencies, such as STACK and WeBWorK, can take student’s answer as a mathematical object, e.g. a function or an equation, and check whether it satisfies the requirements set for a correct answer as well as give immediate and meaningful feedback. That is a powerful tool especially for formative assessment: log data shows that many students prefer to start with quizzes and when necessary, consult lecturing materials. Automated diagnostic tests give students information where they stand before starting to study Calculus and feedback about how to rehearse for that. Peer assessment is also used in online Calculus courses. There students evaluate and give constructive feedback to other students’ work, which should be a complete and clear presentation of a solution to a problem with correct argumentation.
The first requirement for an online mathematics homework engine is to encourage students to practice and reinforce their mathematics skills in ways that are as good or better than traditional paper homework. The use of the computer and the internet should not limit the kind or quality of the mathematics that we teach and if possible it should expand it.
Now that much of the homework practice takes place online we have the potential of a new and much better window into how students learn mathematics but we must continue to ensure that students are studying the mathematics we want to have learned and not just mathematics that is easily gradable. Several of the open source mathematics engines that do this well are represented at this conference.
The WeBWorK mathematics rendering engine started twenty years ago as a stand alone application. Since then homework questions contributed by many, many mathematicians to the OpenProblemLibrary (OPL) have created a collection of over 30,000 Creative Commons licensed problems primarily directed toward calculus but ranging from basic algebra through matrix linear algebra.
I’ll present one of the adaptations of WeBWorK which allows it to render mathematics questions for a standard Moodle quiz in much the same way that STACK functions. Both STACK and WeBWorK vastly increase Moodle’s ability to handle mathematics. Using the Moodle quiz format will make the OPL available to many more educators and allows utilization of Moodle’s facility at collecting student data.
If there is time I’ll show a second adaptation which allows WeBWorK to serve as an assignment type within Moodle. These same mechanisms allow active WeBWorK questions to be embedded in other learning management systems, in interactive textbooks and even HTML pages. This capability fits well with an emerging trend to use smaller, more specialized, inter-operating components for online education.
In this talk I'll introduce the audience to the issues of predictive modelling and identify how it is poised to enable personalized learning at scale. I'll contrast predictive analytic techniques with descriptive inferential techniques, and identify some specific opportunities in higher education for predictive modelling to have significant impact. I'll share some of my own experiments in the area, and conclude with some of the challenges facing educational technology researchers as we move towards more personalized learning ecosystems.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
3. • Student attitudes are related to higher mathematics
achievement
• Expectations of success, comparisons of ability,
academic-self concept, confidence of own ability, etc
(Reyes & Stanic, 1988; Randhawa et al, 1993, House, 1993, House, 1995)
• Cognitive factors are also related to higher
mathematics achievement
• Numerosity, spatial abilities, memory, etc (Halberda et al.,
2008; Siegler & Opfer, 2003; Casey et al., 1995)
• But these aren’t surprising, even for predicting
success in Calculus (and Calculus II)
Understanding which
students are successful
4. • Online learning is becoming more available and
popular
• These courses provide more data related to the “user”
• Every action of the student within the course is tracked
• Can these data be used to understand success in the
course?
• Future goal of intervening with students at risk for
failure early in the course
Understanding which students are
successful in a hybrid Calc course
5. • What are the most important individual differences
predictors of success in a hybrid user-driven
Calculus II course?
• We will examine both clickstream data and
information about students’ attitudes and cognitive
performance
Research Question
6. • Spring 2014 Calculus II course at FSU
• Hybrid course with a flipped classroom
• Students used the online course platform (WEPS
https://myweps.com/moodle/) to watch videos of
the course content and solved problems in class with
professor
• All teaching content was available to students at all
times (graded items time available only)
Methods
7. • Participants
• 84 participants (43% female, 84% White)
• Took ~45min battery of demographics, student
attitudes and cognitive measures (mostly online in
qualtrics)
• Outcome variable
• Final grade (0-100) in Calculus II course
Methods
8. • Math Confidence (adapted from confidence subscale of
Fennema & Sherman, 1976)
• Generally I have felt secure about attempting
mathematics
• I am sure I could do advanced work in mathematics
• I can get good grades in mathematics
• Math has been my worst subject
Attitudinal Measures
9. • Math Anxiety (MARS-R; Plake & Parker, 1982)
• Please indicate the amount of anxiety you feel in each
of the following situations.
• Buying a math textbook.
• Looking through the pages on a math text.
• Having to use tables of formulae.
Attitudinal Measures
10. • Panamath “Dots Task” (Halberda et al., 2008)
• Approximate Number System
• Are there more yellow or blue dots?
Cognitive Measures
12. • So much available information
• How to get it into something useable in more
“traditional” statistical models?
• We just want a number!!!
• Tried to use variables that we thought we had
reasonable interpretations of (but honestly still
unsure)
Online Course Measures
13. • Online workshops (graded homeworks)
• Mean time to submission across 13 workshops
• From 0-100, with 100 being submitted exactly
at time due (from when workshop was
available)
• Mean time to submission of graded workshop
assignments of other students
• From 0-100, with 100 being submitted exactly
at time due (from deadline of workshop)
Online Course Measures
14. • Online quizzes
• Unlimited attempts at quizzes (7 total)
• Sum of total number of attempts
Online Course Measures
16. • Research question: of our key variables of interest,
what are the most useful for predicting final grade?
• Dominance analysis allows for this specific test
(Budescu, 1993; Azen & Budescu, 2003)
• All key variables were added to the model, and pitted
against each other for relative importance
• https://pantherfile.uwm.edu/azen/www/damacro.h
tml
• 1000 bootstrapped samples
Dominance Analysis (DA)
17. • Complete dominance
• (math confidence = quiz attempts = assessment time)
> (math anxiety = mental rotation = ANS = workshop
time)
• Reproducibility quite low (<10%)
• General dominance
• (assessment time > quiz attempts > math confidence >
math anxiety) > (ANS > workshop time > mental
rotation)
• Reproducibility is high across parentheses
DA results
18. • (assessment time > quiz attempts > math confidence >
math anxiety) > (ANS > workshop time > mental rotation)
DA results
0.1
0.09
0.06
0.02
0.02
0.010.005
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Final Grade
Mental Rotation
Workshop Time
ANS
Math Anxiety
Math Confidence
Quiz Attempts
Assessment Time
19. Latent Profile Analysis
• Please keep in mind the following are very
underpowered
• Intention was to have more data for full model
• Simulation studies suggest we need at least n=200 at
first, and to feel comfortable making reliable
predictions with our model likely closer to n = 500
(Nylund, Asparouhov & Muthen, 2007)
21. Final Grade Exam 1 Exam 2 Exam 3 Diagnostic Test
class 1 0.09 0.15 0.07 0.09 0.12
class 2 0.02 -0.32 0.1 -0.05 -0.13
class 3 -1.59 -1.05 -1.56 -1.29 -1.06
-1.8
-1.6
-1.4
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
Score
22. • Student attitudes relatively important
• Replication of previous literature showing math
confidence important positive predictor of
math/Calculus success (e.g., House, 1995)
• Possibly role for measuring math anxiety too
• May be due to this being Calc II
• What happened to the cognitive predictors?
Discussion
23. • Online data also important relative predictors
• Assessment total negative predictor
• “procrastination” variable
• OR, students who struggle in Calculus found this
very hard
• Number of times retake quiz positive predictor
• “perfection” variable
Discussion
24. • We learn more when we look at BOTH:
• student’s interactions with online platform to
prediction of student success AND
• known “psychological” student characteristics
• But SO MUCH data, and most of it requires
huge assumptions
• Hard to know what we are measuring with the
online variables!
Conclusion
25. • What other information can we get from
clickstream data that might be useful?
• How to get it into a useable form?
• Can we predict how students will use the
online system from their characteristics?
• Can we then use this information to develop a
recommendation system?
Future Directions
26. • NSF grants 1450501 & E2030291
• Dr. Olga Caprotti & Yahya Almalki
hart@psy.fsu.edu
@saraannhart
Acknowledgements
ganley@psy.fsu.edu
@colleenganley
Editor's Notes
Added reference for spatial.
Added mars-r cite – you were right initially! We must have switched after this.
When one is mainly concerned with how much scores on the criterion variable would change based on a unit increase in a predictor while holding the other predictors constant, then regression coefficients are well suited to address such a question. However, we believe researchers’ interest in predictor variables extends beyond such simple questions to more fully understand the impact of a particular predictor relative to others in the model. An example of this type of question might be, do certain individual difference variables matter more than others in predicting leader effectiveness? Or, is a particular individual difference variable a meaningful (useful) predictor of leader effectiveness? The central issue in both of these examples concerns how much of the variance explained in leader effectiveness can be attributed to each predictor variable. Such a question is at the heart of what most organizational researchers mean when they talk about predictor importance.
Data is z-scored, these are 3 classes that the data across questionnaires indicated existed. Note that class 3 is very small
Predicting course outcomes from classes made with questionnaire variables