what does teacher entitlement look like? The extreme cases are easy to spot.
If we act in ways that aren’t entitled, ways that treat students with respect, that deliver the quality educational experiences they deserve, our leadership creates a different set of expectations. If we say we’ll have the test/paper/projects grades done by Friday, we meet that deadline.
The difference between student and teacher entitlement is that students have to ask for what they may not deserve. We don’t have to ask. We may apologize for not having the papers graded, but we don’t need to ask for an extension.
The EDUCAUSE Learning Initiative has just launched its 2018 Key Issues in Teaching and Learning Survey, so vote today: http://www.tinyurl.com/ki2018.
Each year, the ELI surveys the teaching and learning community in order to discover the key issues and themes in teaching and learning. These top issues provide the thematic foundation or basis for all of our conversations, courses, and publications for the coming year. Longitudinally they also provide the way to track the evolving discourse in the teaching and learning space. More information about this annual survey can be found at https://www.educause.edu/eli/initiatives/key-issues-in-teaching-and-learning.
ACADEMIC TRANSFORMATION (Holistic models supporting student success, leadership competencies for academic transformation, partnerships and collaborations across campus, IT transformation, academic transformation that is broad, strategic, and institutional in scope)
ACCESSIBILITY AND UNIVERSAL DESIGN FOR LEARNING (Supporting and educating the academic community in effective practice; intersections with instructional delivery modes; compliance issues)
ADAPTIVE TEACHING AND LEARNING (Digital courseware; adaptive technology; implications for course design and the instructor’s role; adaptive approaches that are not technology-based; integration with LMS; use of data to improve learner outcomes)
COMPETENCY-BASED EDUCATION AND NEW METHODS FOR THE ASSESSMENT OF STUDENT LEARNING (Developing collaborative cultures of assessment that bring together faculty, instructional designers, accreditation coordinators, and technical support personnel, real world experience credit)
DIGITAL AND INFORMATION LITERACIES (Student and faculty literacies; research skills; data discovery, management, and analysis skills; information visualization skills; partnerships for literacy programs; evaluation of student digital competencies; information evaluation)
EVALUATING TECHNOLOGY-BASED INSTRUCTIONAL INNOVATIONS (Tools and methods to gather data;data analysis techniques; qualitative vs. quantitative data; evaluation project design; using findings to change curricular practice; scholarship of teaching and learning; articulating results to stakeholders; just-in-time evaluation of innovations). here is my bibliographical overview on Big Data (scroll down to “Research literature”: http://blog.stcloudstate.edu/ims/2017/11/07/irdl-proposal/ )
EVOLUTION OF THE TEACHING AND LEARNING SUPPORT PROFESSION (Professional skills for T&L support; increasing emphasis on instructional design; delineating the skills, knowledge, business acumen, and political savvy for success; role of inter-institutional communities of practices and consortia; career-oriented professional development planning)
FACULTY DEVELOPMENT (Incentivizing faculty innovation; new roles for faculty and those who support them; evidence of impact on student learning/engagement of faculty development programs; faculty development intersections with learning analytics; engagement with student success)
GAMIFICATION OF LEARNING (Gamification designs for course activities; adaptive approaches to gamification; alternate reality games; simulations; technological implementation options for faculty)
INTEGRATED PLANNING AND ADVISING FOR STUDENT SUCCESS (Change management and campus leadership; collaboration across units; integration of technology systems and data; dashboard design; data visualization (here previous blog postings on this issue: http://blog.stcloudstate.edu/ims?s=data+visualization); counseling and coaching advising transformation; student success analytics)
LEARNING ANALYTICS (Leveraging open data standards; privacy and ethics; both faculty and student facing reports; implementing; learning analytics to transform other services; course design implications)
LEARNING SPACE DESIGNS (Makerspaces; funding; faculty development; learning designs across disciplines; supporting integrated campus planning; ROI; accessibility/UDL; rating of classroom designs)
MICRO-CREDENTIALING AND DIGITAL BADGING (Design of badging hierarchies; stackable credentials; certificates; role of open standards; ways to publish digital badges; approaches to meta-data; implications for the transcript; Personalized learning transcripts and blockchain technology (here previous blog postings on this issue: http://blog.stcloudstate.edu/ims?s=blockchain)
MOBILE LEARNING (Curricular use of mobile devices (here previous blog postings on this issue:
MULTI-DIMENSIONAL TECHNOLOGIES (Virtual, augmented, mixed, and immersive reality; video walls; integration with learning spaces; scalability, affordability, and accessibility; use of mobile devices; multi-dimensional printing and artifact creation)
NEXT-GENERATION DIGITAL LEARNING ENVIRONMENTS AND LMS SERVICES (Open standards; learning environments architectures (here previous blog postings on this issue: http://blog.stcloudstate.edu/ims/2017/03/28/digital-learning/; social learning environments; customization and personalization; OER integration; intersections with learning modalities such as adaptive, online, etc.; LMS evaluation, integration and support)
ONLINE AND BLENDED TEACHING AND LEARNING (Flipped course models; leveraging MOOCs in online learning; course development models; intersections with analytics; humanization of online courses; student engagement)
OPEN EDUCATION (Resources, textbooks, content; quality and editorial issues; faculty development; intersections with student success/access; analytics; licensing; affordability; business models; accessibility and sustainability)
PRIVACY AND SECURITY (Formulation of policies on privacy and data protection; increased sharing of data via open standards for internal and external purposes; increased use of cloud-based and third party options; education of faculty, students, and administrators)
WORKING WITH EMERGING LEARNING TECHNOLOGY (Scalability and diffusion; effective piloting practices; investments; faculty development; funding; evaluation methods and rubrics; interoperability; data-driven decision-making)
he EDUCAUSE Blended and Online Learning Constituent Group Listserv
Quick poll – do you require your faculty to be trained how to teach online before they are allowed to teach an online course at your institution?
Kristen Brown, Assistant Director, UofL Online
YES. Our faculty are required to complete two classes. One on using the LMS and the other is a 5-week moderated course called Teaching Online. Both courses are offered online.
Linda C. Morosko, MA Director, eStarkState Division of Student Success
Chad Maxson, EdD │ Dean of Online Learning, Olivet Nazarene University │ Center for Teaching and Learning One University Avenue │ Bourbonnais, IL 60914
Gina Okun Assistant Dean, Online Berkeley College 64 East Midland Avenue, Suite 2 Paramus, NJ 07652
The online academic program director (i.e. MBA, M.Ed.) and I meet with each new instructor to go materials that cover providing instructor presence and best practices in general. I also ask that they sign something that lists 14 online teaching practices we expect as an institution. They also have to complete some LMS training so that they can post announcements, participate in discussions, and manage their gradebook.
We are currently designing a more formal 6 hour online training that is required.
Course design is separate and that’s a 16 week process with our designers.
Tex Brieger Director of Distance Education (814) 871-7134
Absolutely. Also, we give them a stipend to attend the training and develop and online course.
Linda S. Futch, Ed.D. Department Head, Course Design and Development Center for Distributed Learning University of Central Florida
I think the bigger need is for ongoing training for recertification to teach online as technology and online pedagogical models evolve over time.
Kelvin Kelvin Bentley <timelord33@GMAIL.COM>
At Suffolk yes, we do. Over time that went from essentially “how to make the LMS work” to a Faculty Academy where faculty spend an entire semester working as a cohort to examine online pedagogy and best practices. The latter works much better for sound course development.
Doug Kahn College Assistant Dean for IT Operations Suffolk County Community College 533 College Road Selden, NY 11784
I can’t speak of other accrediting bodies, but SACS-COC is fairly clear in its documentation that faculty should be adequately trained before teaching online. Prior to my arrival at U of R in 2015, I worked for 20 years at E. Carolina U. which has a large assortment of online programs and courses. I assisted in the process of designing several online training modules that were to serve as “basic training” (with assessments) for online instructors…directly due to needing to meet accreditation guidelines. As part of documentation for reaffirmation/reaccreditation, had to provide documentation showing that faculty had successfully completed the training. I believe it is required to complete every three years.
Michael Dixon, Assistant Director Center for Teaching, Learning & Technology University of Richmond
I wish we did, but we do not. We run up against contract issues with. Certainly, this could be changed with institutional will but would require a shift in how our agreements with the faculty union.
TRAVIS FREEMAN, MFA EDUCATIONAL DEVELOPER FACULTY AND CURRICULUM DEVELOPMENT CENTRE (FCDC) Office Location: 113 McCaul St, Room 501 T 416 977 6000 x3358 Etfreeman@ocadu.ca
Librarians in universities, colleges, and community colleges can establish, assess, and link
academic library outcomes to institutional outcomes related to the following areas:
student enrollment, student retention and graduation rates, student success, student
achievement, student learning, student engagement, faculty research productivity,
faculty teaching, service, and overarching institutional quality.
Assessment management systems help higher education educators, including librarians, manage their outcomes, record and maintain data on each outcome, facilitate connections to
similar outcomes throughout an institution, and generate reports.
Assessment management systems are helpful for documenting progress toward
strategic/organizational goals, but their real strength lies in managing learning
to determine the impact of library interactions on users, libraries can collect data on how individual users engage with library resources and services.
increase library impact on student enrollment.
p. 13-14improved student retention and graduation rates. High -impact practices include: first -year seminars and experiences, common intellectual experiences, learning communities, writing – intensive courses, collaborative assignments and projects, undergraduate research, Value of Academic Libraries diversity/global learning, service learning/community -based learning, internships, capstone courses and projects
Libraries support students’ ability to do well in internships, secure job placements, earn salaries, gain acceptance to graduate/professional schools, and obtain marketable skills.
librarians can investigate correlations between student library interactions and their GPA well as conduct test item audits of major professional/educational tests to determine correlations between library services or resources and specific test items.
p. 15 Review course content, readings, reserves, and assignments.
Track and increase library contributions to faculty research productivity.
Continue to investigate library impact on faculty grant proposals and funding, a means of generating institutional income. Librarians contribute to faculty grant proposals in a number of ways.
Demonstrate and improve library support of faculty teaching.
p. 20 Internal Focus: ROI – lib value = perceived benefits / perceived costs
production of a commodity – value=quantity of commodity produced × price per unit of commodity
p. 21 External focus
a fourth definition of value focuses on library impact on users. It asks, “What is the library trying to achieve? How can librarians tell if they have made a difference?” In universities, colleges, and community colleges, libraries impact learning, teaching, research, and service. A main method for measuring impact is to “observe what the [users] are actually doing and what they are producing as a result”
A fifth definition of value is based on user perceptions of the library in relation to competing alternatives. A related definition is “desired value” or “what a [user] wants to have happen when interacting with a [library] and/or using a [library’s] product or service” (Flint, Woodruff and Fisher Gardial 2002) . Both “impact” and “competing alternatives” approaches to value require libraries to gain new understanding of their users’ goals as well as the results of their interactions with academic libraries.
p. 23 Increasingly, academic library value is linked to service, rather than products. Because information products are generally produced outside of libraries, library value is increasingly invested in service aspects and librarian expertise.
service delivery supported by librarian expertise is an important library value.
p. 25 methodology based only on literature? weak!
p. 26 review and analysis of the literature: language and literature are old (e.g. educational administrators vs ed leaders).
G government often sees higher education as unresponsive to these economic demands. Other stakeholder groups —students, pa rents, communities, employers, and graduate/professional schools —expect higher education to make impacts in ways that are not primarily financial.
Because institutional missions vary (Keeling, et al. 2008, 86; Fraser, McClure and
Leahy 2002, 512), the methods by which academic libraries contribute value vary as
well. Consequently, each academic library must determine the unique ways in which they contribute to the mission of their institution and use that information to guide planning and decision making (Hernon and Altman, Assessing Service Quality 1998, 31) . For example, the University of Minnesota Libraries has rewritten their mission and vision to increase alignment with their overarching institution’s goals and emphasis on strategic engagement (Lougee 2009, allow institutional missions to guide library assessment
Assessment vs. Research
In community colleges, colleges, and universities, assessment is about defining the
purpose of higher education and determining the nature of quality (Astin 1987)
Academic libraries serve a number of purposes, often to the point of being
Assessment “strives to know…what is” and then uses that information to change the
status quo (Keeling, et al. 2008, 28); in contrast, research is designed to test
hypotheses. Assessment focuses on observations of change; research is concerned with the degree of correlation or causation among variables (Keeling, et al. 2008, 35) . Assessment “virtually always occurs in a political context ,” while research attempts to be apolitical” (Upcraft and Schuh 2002, 19) .
p. 31 Assessment seeks to document observations, but research seeks to prove or disprove ideas. Assessors have to complete assessment projects, even when there are significant design flaws (e.g., resource limitations, time limitations, organizational contexts, design limitations, or political contexts); whereas researchers can start over (Upcraft and Schuh 2002, 19) . Assessors cannot always attain “perfect” studies, but must make do with “good enough” (Upcraft and Schuh 2002, 18) . Of course, assessments should be well planned, be based on clear outcomes (Gorman 2009, 9- 10) , and use appropriate methods (Keeling, et al. 2008, 39) ; but they “must be comfortable with saying ‘after’ as well as ‘as a result of’…experiences” (Ke eling, et al. 2008, 35) .
Two multiple measure approaches are most significant for library assessment: 1) triangulation “where multiple methods are used to find areas of convergence of data from different methods with an aim of overcoming the biases or limitations of data gathered from any one particular method” (Keeling, et al. 2008, 53) and 2) complementary mixed methods , which “seek to use data from multiple methods to build upon each other by clarifying, enhancing, or illuminating findings between or among methods” (Keeling, et al. 2008, 53) .
p. 34 Academic libraries can help higher education institutions retain and graduate students, a keystone part of institutional missions (Mezick 2007, 561) , but the challenge lies in determining how libraries can contribute and then document their contribution
p. 35. Student Engagement: In recent years, academic libraries have been transformed to provide “technology and content ubiquity” as well as individualized support My Note: I read the “technology and content ubiquity” as digital literacy / metaliteracies, where basic technology instructional sessions (everything that IMS offers for years) is included, but this library still clenches to information literacy only.
In the past, academic libraries functioned primarily as information repositories; now they are becoming learning enterprises (Bennett 2009, 194) . This shift requires academic librarians to embed library services and resources in the teaching and learning activities of their institutions (Lewis 2007) . In the new paradigm, librarians focus on information skills, not information access (Bundy 2004, 3); they think like educators, not service providers (Bennett 2009, 194) .
p. 38. For librarians, the main content area of student learning is information literacy; however, they are not alone in their interest in student inform ation literacy skills (Oakleaf, Are They Learning? 2011). My note: Yep. it was. 20 years ago. Metaliteracies is now.
p. 41 surrogates for student learning in Table 3.
p. 42 strategic planning for learning:
According to Kantor, the university library “exists to benefit the students of the educational institution as individuals ” (Library as an Information Utility 1976 , 101) . In contrast, academic libraries tend to assess learning outcomes using groups of students
p. 45 Assessment Management Systems
Each assessment management system has a slightly different set of capabilities. Some guide outcomes creation, some develop rubrics, some score student work, or support student portfolios. All manage, maintain, and report assessment data
p. 46 faculty teaching
However, as online collections grow and discovery tools evolve, that role has become less critical (Schonfeld and Housewright 2010; Housewright and Schonfeld, Ithaka’s 2006 Studies of Key Stakeholders 2008, 256) . Now, libraries serve as research consultants, project managers, technical support professionals, purchasers , and archivists (Housewright, Themes of Change 2009, 256; Case 2008) .
Librarians can count citations of faculty publications (Dominguez 2005)
Tenopir, C. (2012). Beyond usage: measuring library outcomes and value. Library Management, 33(1/2), 5-13.
methods that can be used to measure the value of library products and services. (Oakleaf, 2010; Tenopir and King, 2007): three main categories
Implicit value. Measuring usage through downloads or usage logs provide an implicit measure of value. It is assumed that because libraries are used, they are of value to the users. Usage of e-resources is relatively easy to measure on an ongoing basis and is especially useful in collection development decisions and comparison of specific journal titles or use across subject disciplines.
do not show purpose, satisfaction, or outcomes of use (or whether what is downloaded is actually read).
Explicit methods of measuring value include qualitative interview techniques that ask faculty members, students, or others specifically about the value or outcomes attributed to their use of the library collections or services and surveys or interviews that focus on a specific (critical) incident of use.
Derived values, such as Return on Investment (ROI), use multiple types of data collected on both the returns (benefits) and the library and user costs (investment) to explain value in monetary terms.
Cognitive load theory is built upon two commonly accepted ideas. The first is that there is a limit to how much new information the human brain can process at one time. The second is that there are no known limits to how much stored information can be processed at one time. The aim of cognitive load research is therefore to develop instructional techniques and recommendations that fit within the characteristics of working memory, in order to maximise learning.
Explicit instruction involves teachers clearly showing students what to do and how to do it, rather than having students discover or construct information for themselves
how working memory and long-term memory process and store information
Working memory is the memory system where small amounts of information are stored for a very short duration (RAM). Long-term memory is the memory system where large amounts of information are stored semi-permanently (hard drive)
Cognitive load theory assumes that knowledge is stored in long- term memory in the form of ‘schemas’ 2 . A schema organises elements of information according to how they will be used. According to schema theory, skilled performance is developed through building ever greater numbers of increasingly complex schemas by combining elements of lower level schemas into higher level schemas. There is no limit to how complex schemas can become. An important process in schema construction is automation, whereby information can be processed automatically with minimal conscious effort. Automaticity occurs after extensive practice
Schemas provide a number of important functions that are relevant to learning. First, they provide a system for organising and storing knowledge. Second, and crucially for cognitive load theory, they reduce working memory load. This is because, although there are a limited number of elements that can be held in working memory at one time, a schema constitutes only a single element in working memory. In this way, a high level schema – with potentially infinite informational complexity – can effectively bypass the limits of working memory
Types of cognitive load
Cognitive load theory identifies three different types of cognitive load: intrinsic, extraneous and germane load
Intrinsic cognitive load relates to the inherent difficulty of the subject matter being learnt.
subject matter that is difficult for a novice may be very easy for an expert.
Extraneous cognitive load relates to how the subject matter is taught.
extraneous load is the ‘bad’ type of cognitive load, because it does not directly contribute to learning. Cognitive load theorists consider that instructional design will be most effective when it minimises extraneous load in order to free up the capacity of working memory
Germane cognitive load refers to the load imposed on the working memory by the process of learning – that is, the process of transferring information into the long-term memory through schema construction
the approach of decreasing extraneous cognitive load while increasing germane cognitive load will only be effective if the total cognitive load remains within the limits of working memory
The survey findings are from the responses of 109 deans of four-year colleges and universities in March and April 2017. Of the respondents, 61 percent were from public universities and 60 percent have been in their jobs at least five years.
Deans were divided on whether faculty members get enough support in teaching courses online–43 percent said faculty are getting shortchanged in how much help they get in rethinking their courses and teaching with technology, while 40 percent said they believe they are getting enough support and 14 percent are neutral.
One-third of deans agree online courses are comparable to face-to-face courses, and roughly the same proportion said they disagree.
Thirty-seven percent of college deans surveyed described the pace of change at their own institutions as “too slow.” Deans surveyed cite lack of money being the biggest hurdle to change, followed by resource constraints on faculty and staff and a resistance or aversion to change.
Empathy Is Tough to Teach, But Is One Of the Most Important Life Lessons
Dr. Brené Brown has become famous for her speaking and writing about vulnerability, worthiness, shame and the other important emotions running underneath daily life all the time. One theme she returns to over and over is the importance of cultivating empathy, a very different reaction than sympathy.
Children have opportunities to learn empathy from their parents, but also from their teachers and peers.
STEAM (Science, Technology, Engineering ,Art, and Math) tools to use in your classroom
provide teachers with a handy resource to use with their students to help them develop critical thinking skills and adopt ‘an engineering or design approach towards real-world problems while building on their mathematics and science base’.