Building Real-Time BI Systems with Kafka, Spark, and Kudu: Spark Summit East ...Spark Summit
One of the key challenges in working with real-time and streaming data is that the data format for capturing data is not necessarily the optimal format for ad hoc analytic queries. For example, Avro is a convenient and popular serialization service that is great for initially bringing data into HDFS. Avro has native integration with Flume and other tools that make it a good choice for landing data in Hadoop. But columnar file formats, such as Parquet and ORC, are much better optimized for ad hoc queries that aggregate over large number of similar rows.
a simple presentation about different big data stream processing systems such as SPARK, SAMZA and STORM and the difference between their architectures and purpose, in addition we talk about streaming layers tools such as Kafka and rabbitMQ, this presentation refer to this paper
https://vsis-www.informatik.uni-hamburg.de/getDoc.php/publications/561/Real-time%20stream%20processing%20for%20Big%20Data.pdf and other useful links.
February 2017 HUG: Exactly-once end-to-end processing with Apache ApexYahoo Developer Network
Apache Apex (http://apex.apache.org/) is a stream processing platform that helps organizations to build processing pipelines with fault tolerance and strong processing guarantees. It was built to support low processing latency, high throughput, scalability, interoperability, high availability and security. The platform comes with Malhar library - an extensive collection of processing operators and a wide range of input and output connectors for out-of-the-box integration with an existing infrastructure. In the talk I am going to describe how connectors together with the distributed checkpointing (a mechanism used by the Apex to support fault tolerance and high availability) provide exactly-once end-to-end processing guarantees.
Speakers:
Vlad Rozov is Apache Apex PMC member and back-end engineer at DataTorrent where he focuses on the buffer server, Apex platform network layer, benchmarks and optimizing the core components for low latency and high throughput. Prior to DataTorrent Vlad worked on distributed BI platform at Huawei and on multi-dimensional database (OLAP) at Hyperion Solutions and Oracle.
Building Real-Time BI Systems with Kafka, Spark, and Kudu: Spark Summit East ...Spark Summit
One of the key challenges in working with real-time and streaming data is that the data format for capturing data is not necessarily the optimal format for ad hoc analytic queries. For example, Avro is a convenient and popular serialization service that is great for initially bringing data into HDFS. Avro has native integration with Flume and other tools that make it a good choice for landing data in Hadoop. But columnar file formats, such as Parquet and ORC, are much better optimized for ad hoc queries that aggregate over large number of similar rows.
a simple presentation about different big data stream processing systems such as SPARK, SAMZA and STORM and the difference between their architectures and purpose, in addition we talk about streaming layers tools such as Kafka and rabbitMQ, this presentation refer to this paper
https://vsis-www.informatik.uni-hamburg.de/getDoc.php/publications/561/Real-time%20stream%20processing%20for%20Big%20Data.pdf and other useful links.
February 2017 HUG: Exactly-once end-to-end processing with Apache ApexYahoo Developer Network
Apache Apex (http://apex.apache.org/) is a stream processing platform that helps organizations to build processing pipelines with fault tolerance and strong processing guarantees. It was built to support low processing latency, high throughput, scalability, interoperability, high availability and security. The platform comes with Malhar library - an extensive collection of processing operators and a wide range of input and output connectors for out-of-the-box integration with an existing infrastructure. In the talk I am going to describe how connectors together with the distributed checkpointing (a mechanism used by the Apex to support fault tolerance and high availability) provide exactly-once end-to-end processing guarantees.
Speakers:
Vlad Rozov is Apache Apex PMC member and back-end engineer at DataTorrent where he focuses on the buffer server, Apex platform network layer, benchmarks and optimizing the core components for low latency and high throughput. Prior to DataTorrent Vlad worked on distributed BI platform at Huawei and on multi-dimensional database (OLAP) at Hyperion Solutions and Oracle.
AMIS SIG - Introducing Apache Kafka - Scalable, reliable Event Bus & Message ...Lucas Jellema
Introduction of Apache Kafka - the open source platform for real time message queuing and reliable, scalable, distributed event handling and high volume pub/sub implementation.
see GitHub https://github.com/MaartenSmeets/kafka-workshop for the workshop resources.
How to Integrate Spark MLlib and Apache Solr to Build Real-Time Entity Type R...Spark Summit
Understanding the types of entities expressed in a search query (Company, Skill, Job Title, etc.) enables more intelligent information retrieval based upon those entities compared to a traditional keyword-based search. Because search queries are typically very short, leveraging a traditional bag-of-words model to identify entity types would be inappropriate due to the lack of contextual information. We implemented a novel entity type recognition system which combines clues from different sources of varying complexity in order to collect real-world knowledge about query entities. We employ distributional semantic representations of query entities through two models: 1) contextual vectors generated from encyclopedic corpora like Wikipedia, and 2) high dimensional word embedding vectors generated from millions of job postings using Spark MLlib. In order to enable real-time recognition of entity types, we utilize Apache Solr to cache the embedding vectors generated by Spark MLlib. This approach enable us to recognize entity types for entities expressed in search queries in less than 60 milliseconds which makes this system applicable for real-time entity type recognition.
Building Realtime Data Pipelines with Kafka Connect and Spark Streaming: Spar...Spark Summit
Spark Streaming makes it easy to build scalable, robust stream processing applications — but only once you’ve made your data accessible to the framework. If your data is already in one of Spark Streaming’s well-supported message queuing systems, this is easy. If not, an ad hoc solution to import data may work for a single application, but trying to scale that approach to complex data pipelines integrating dozens of data sources and sinks with multi-stage processing quickly breaks down. Spark Streaming solves the realtime data processing problem, but to build large scale data pipeline we need to combine it with another tool that addresses data integration challenges.
The Apache Kafka project recently introduced a new tool, Kafka Connect, to make data import/export to and from Kafka easier. This talk will first describe some data pipeline anti-patterns we have observed and motivate the need for a tool designed specifically to bridge the gap between other data systems and stream processing frameworks. We will introduce Kafka Connect, starting with basic usage, its data model, and how a variety of systems can map to this model. Next, we’ll explain how building a tool specifically designed around Kafka allows for stronger guarantees, better scalability, and simpler operationalization compared to other general purpose data copying tools. Finally, we’ll describe how combining Kafka Connect and Spark Streaming, and the resulting separation of concerns, allows you to manage the complexity of building, maintaining, and monitoring large scale data pipelines.
Modern businesses have data at their core, and this data is changing continuously. How can we harness this torrent of information in real-time? The answer is stream processing, and the technology that has since become the core platform for streaming data is Apache Kafka. Among the thousands of companies that use Kafka to transform and reshape their industries are the likes of Netflix, Uber, PayPal, and AirBnB, but also established players such as Goldman Sachs, Cisco, and Oracle.
Unfortunately, today’s common architectures for real-time data processing at scale suffer from complexity: there are many technologies that need to be stitched and operated together, and each individual technology is often complex by itself. This has led to a strong discrepancy between how we, as engineers, would like to work vs. how we actually end up working in practice.
In this session we talk about how Apache Kafka helps you to radically simplify your data processing architectures. We cover how you can now build normal applications to serve your real-time processing needs — rather than building clusters or similar special-purpose infrastructure — and still benefit from properties such as high scalability, distributed computing, and fault-tolerance, which are typically associated exclusively with cluster technologies. Notably, we introduce Kafka’s Streams API, its abstractions for streams and tables, and its recently introduced Interactive Queries functionality. As we will see, Kafka makes such architectures equally viable for small, medium, and large scale use cases.
As a data integration professional, it’s almost a guarantee that you’ve heard of real-time stream processing of Big Data. The usual players in the open source world are Apache Kafka, used to move data in real-time, and Spark Streaming, built for in-flight transformations. But what about relational data? Quite often we forget that products incubated in the Apache Foundation can also serve a purpose for “standard” relational databases as well. But how? Well, let’s introduce Oracle GoldenGate and Oracle Data Integrator for Big Data. GoldenGate can extract relational data in real time and produce Kafka messages, ensuring relational data is a part of the enterprise data bus. These messages can then be ingested via ODI through a Spark Streaming process, integrating with additional data sources, such as other relational tables, flat files, etc, as needed. Finally, the output can be sent to multiple locations: on through to a data warehouse for analytical reporting, back to Kafka for additional targets to consume, or any number of targets. Attendees will walk away with a framework on which they can build their data streaming projects, combining relational data with big data and using a common, structured approach via the Oracle Data Integration product stack.
Presented at BIWA Summit 2017.
Comparison of Open Source Frameworks for Integrating the Internet of ThingsKai Wähner
Session from JFokus 2017 (https://www.jfokus.se/jfokus/talks.jsp#ComparisonofOpenSour) in Stockholm, Sweden.
This session shows and compares open source frameworks built to develop very lightweight applications or microservices, which can be deployed on small devices with very low resources and wire together all different kinds of hardware devices, APIs and online services. The focus of this session is the comparison of open source projects such as Node-RED or Flogo, which offer a zero-code environment with web IDE for building and deploying integration and data processing directly onto connected devices using IoT standards such as MQTT, WebSockets or CoaP, but also other interfaces such as Twitter feeds or REST services. The end of the session compares these open source projects to other options such as SaaS offerings like AWS IoT or more powerful streaming analytics platforms.
Architectual Comparison of Apache Apex and Spark StreamingApache Apex
This presentation discusses architectural differences between Apache Apex features with Spark Streaming. It discusses how these differences effect use cases like ingestion, fast real-time analytics, data movement, ETL, fast batch, very low latency SLA, high throughput and large scale ingestion.
Also, it will cover fault tolerance, low latency, connectors to sources/destinations, smart partitioning, processing guarantees, computation and scheduling model, state management and dynamic changes. Further, it will discuss how these features affect time to market and total cost of ownership.
cytoscape is open source network analyses tools, in this slides we define the basic features of this tool, and a brief tutorial of how can you use this tool in innovative way.
Distributed Stream Processing with Apache KafkaJay Kreps
A modern business operates 24/7 and generates data continuously. Shouldn’t we process it continuously too?
A rich ecosystem of real-time data-processing frameworks, tools and systems has been forming around Apache Kafka that allows data to be processed continuously as it occurs. This talk will introduce Kafka and explain why it has become the de facto standard for streaming data. It draws on practical experience building stream-processing applications to discuss the difference between architectures and the challenges each presents. It outlines the streams API in Kafka, and explains how it helps tame some of the complexity in real-time architectures.
Machine Learning Applied to Real Time Scoring in Manufacturing and Energy Uti...Kai Wähner
Kai Wähner (@KaiWaehner) is a Technology Evangelist and Community Director at TIBCO Software - a leading provider of integration and analytics middleware. Kai is an experience guy in broad variety of topics like Big Data, Advanced Analytics & Machine Learning, he loves to write articles and blog about new technologies and make talks. The talk is about 3 different projects where Kai's team built analytic models with technologies R, Apache Spark or H2O.ai which were deployed to real time processing. The use cases include predictive maintenance in manufacturing but also fraud detection in banking and context-specific pricing in insurance. For one of the cases, Kai gonna show detailed steps will be, how it was built and deployed using supervised/unsupervised ML.
Talk was done together with my colleague Ankitaa Bhowmick.
E-Learning or Classroom Learning - Which is Better.pdfChloe Cheney
Do you ever wonder which learning method is more suited for you? Don’t know yet? This article will allow you to weigh e-learning against classroom learning.
Preparing to Teach... a Model for Training FacultyJLewisGeology
This session presents five of the underlying principles guiding the approach used in the Preparing To Teach Online and Hybrid courses at Madison College. This presentation was presented at the Madison College Flexible Learning Conference on October, 18, 2013.
Online Teaching Basics: what I continue to learnJLewisGeology
This is presentation was presented to the Koinonia Professional Development seminar group at the Princeton Theological Seminary on Wednesday, November 14, 2012.
Top Ten Aspects (and Lessons Learned) of a Successful Online Faculty Training...JLewisGeology
This presentation will be presented at the 2012 SLOAN-C International Conference on Online Learning and will share data, lessons, learned, and strategies for success for an online instructor training course offered at Madison College. See the full presentation details and description here: http://sloanconsortium.org/conference/2012/aln/top-ten-aspects-and-lessons-learned-successful-online-faculty-training-program
Note for online courses at Madison CollegeJLewisGeology
This is the standardized note for all online classes at Madison College. Students see this note attached to the course in our course schedule PRIOR to registering for the class. Instructors have an option to add a customizable note for their course sections as described at the bottom of this document.
Orientation for Online Learners at Madison CollegeJLewisGeology
This presentation will be presented at the 2012 SLOAN-C International Conference on Online Learning. See the full presentation details and description here: http://sloanconsortium.org/conference/2012/aln/orientation-online-learners-madison-college
Embracing GenAI - A Strategic ImperativePeter 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.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
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.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Instructions for Submissions thorugh G- Classroom.pptx
PTTO Syllabus, Fall 2012
1. Preparing to Teach Online SYLLABUS
Madison College Professional Development Course
8-week format: September 10th through November 5th, 2012
INSTRUCTOR INFORMATION
Instructor: Jennifer Lewis
Office: Truax 335D.
Office Telephone: (608) 246-6277.
GoogleVoice: (608) 616-9167. Use this number to contact me at home. It will ring my cell
phone or home phone depending on my location. You may also send text messages to this
number.
Email: jlnielsen@madisoncollege.edu
Office Hours: I will be primarily off campus, so face-to-face meetings will be less common —
but I can meet with you whenever you’d like by phone or email.
Skype Name: Jennifer.L.Nielsen. I am available by Skype whenever I am at my computer, so
feel free to chat with me whenever I am online.
CLASS INFORMATION:
Course Description: Preparing To Teach Online (PTTO) provides an introduction to the design and
pedagogy of online teaching and learning. This course provides the opportunity to gain experience
in e-learning environments and online facilitation best practices, the opportunity to receive
instructional design advice while designing a specific course and constructing specific online
teaching materials, the opportunity to create online syllabus policies, and the opportunity to create
an ongoing learning plan to improve your online pedagogy, management, and technical skills.
Participants will explore online teaching methods, communication and interaction management, use
a variety of communication and assessment tools, and distinguish best practices in the online
classroom. This is not a course in tools or Blackboard usage; the focus is on how to design and
facilitate online instruction.
After completing this course, you will be ready to facilitate an existing online course in the next
semester. If you are creating an online course from scratch, your course will be ready in two
semesters.
Credits: You need to choose what kind of credit you are seeking from this course. This course can
earn 2 continuing education credits toward re-certification beyond the probationary level. If you are
still on the initial probation period, you may earn WTCS provisional certification credit for WTCS #52,
teaching methods. You may earn 2 undergraduate or graduate credits through UW-Platteville, for an
additional fee.
Course Format –This course is offered in a 100% online format. Assignments are given in weekly units,
and involve online weekly discussion, reading, audio and video presentations, quizzes, collaborative
writing, and individual writing. This is an 8-week course, which requires 5 hours per week to complete.
Class Deadlines: All weekly assignments for this course are due by 11:59pm every Monday night. You
may work on assignments whenever you like throughout the week, but you must complete all weekly
assignments before Monday night. Please note that this course requires online discussion, which works
best if you log in at a minimum of twice during the week, once between Tuesday and Thursday and
once between Thursday and Monday night.
Pre-requisites: You need to have completed the Madison College course Enhancing Your Course
Preparing to Teach Online 1
2. with Blackboard or the equivalent. Additionally, I strongly recommend that you have the following
skills and technology:
• a high-speed connection to the internet
• basic typing skills
• a webcam and/or microphone that works with your computer.
• A Blackboard master course for the course you plan to teach online in the near future.
Textbook: No textbook required. All textbooks and readings are available in our classroom, free of
charge.
Supplies: Please obtain access to a webcam OR microphone for some assignments; if you plan to
teach online, you will find these devices very helpful. You may wish to obtain a storage device, such
as a USB drive to save/backup your work.
Class participation: This course is designed to provide a forum in which you, as a practicing
professional, can work together with others to build your online course construction and online
facilitation skills. Many of the learning activities are designed to be hands-on and collaborative.
Participation is important for each participant’s professional growth and to the learning of the other
participants. Participation is defined as:
• Sharing your ideas and examples during in class discussions and in online discussion forums
• Asking and responding to questions within the course in a professional, respectful manner
• Posting meaningful responses to other classmates while respecting other opinions and
perspectives
• Completing all activities, as assigned.
In other words, just entering the Blackboard classroom isn’t enough; participation means interaction.
COURSE COMPETENCIES: You have the opportunity to learn the following skills in this course:
• Facilitate online activities
• Create an online learning community
• Encourage student engagement online
• Conduct ongoing and frequent assessments appropriate to the online learning environment.
• Design learning activities that are interactive, to fit different learning styles online.
• Select a content format that suits your specific course outcomes/competencies, delivery
strategy, and technology.
• Utilize appropriate online course organization and structure.
• Evaluate course effectiveness using Madison College Online course quality standards as
appropriate.
• Manage online communication and interaction
• Promote student to students interaction as appropriate
• Develop group management techniques online as appropriate
• Manage student questions, demands, and feedback effectively
• Use a variety of communication tools and strategies.
COMMUNICATION POLICIES AND INFORMATION: I respond to email or phone messages within 24
hours between 9am and 4pm Monday through Friday. I do NOT CHECK my email on the weekends.
Preparing to Teach Online 2
3. Tuesday Blog Announcement: Every Tuesday morning before 12pm, I will create a new posting on our
Blackboard classroom. Please log in and read the information in the entry screen each week.
Instructor Feedback/Response Timeline: I make every effort to grade any work you have submitted
within one week of the date you submitted it. If I am running late, I will do my best to let you know
when you can expect feedback from me. You will receive personal feedback from me on at least
one assignment each week in addition to a grade; you will receive peer feedback or automated
feedback on most assignments.
Netiquette: If you are unfamiliar with online culture or are unfamiliar with "netiquette," you may
appreciate a review of some guidelines covering email, IMing, and Listservs and the like.
Please do not forward any emails or documents from your colleagues in this course without their
knowledge and/or permission. You may forward my emails or documents to anyone you think might
find them helpful; however, please do not forward anything that violates your own or others’ FERPA
rights.
Required email: I will communicate with you using your official Madison College email address, the
one that ends in @matcmadison.edu. Please email me from your official email account OR through
Blackboard; I may not open emails from unknown domains for security reasons. You are responsible
for monitoring your Madison College e-mail account at least twice a week for the duration of this
course.
ACADEMIC RESPONSIBILITIES AND POLICIES:
Student Responsibilities: Students are expected to be familiar with Madison College policies and
procedures. Many of the important policies and procedures are on the Madison College website.
Because this class is online, you should also be aware of the computer use guidelines, which govern
acceptable computer interaction at Madison College.
Academic Integrity/Copyright is an expectation in all Madison College classes. I do expect you to do
your own work. However, you are welcome to copy, steal, or otherwise use anything created by
current or former instructors of this course as though they were your own. Any materials created by
current or former PTTO instructors may be used or reused in entirety or in part for teaching purposes at
Madison College.
However, please respect copyright on all other readings and documents that I did NOT create,
including the work of your classmates. Do not copy from your classmate’s work in this course without
getting permission from them, including collaboratively written documents.
Withdrawing from the Class: If your plans change and you find yourself unable to continue the class,
please notify your instructor right away via email.
Disability Act Statement: Madison College complies with all provisions of the Americans with
Disabilities Act and makes reasonable accommodations upon request.
If you have a disability which requires academic accommodations, please explain it to me via email
or telephone so we can discuss the accommodations that you might need in this class. It is best to
request these accommodations at the beginning if not before class so there is ample time to make
the accommodations.
Learner Responsibilities: As a student in this class, I expect you to:
Preparing to Teach Online 3
4. • take responsibility for your own learning.
• be prepared and be an enthusiastic participant
• treat others with tolerance and respect
• act responsibly and reliably in group work and group discussions
• set high standards for your work
Instructor Responsibilities: As your instructor, I commit to:
• communicating openly and frequently via with you about this class, including weekly emails
and blog postings in our classroom every Tuesday before 12pm.
• maintaining a professional, safe learning environment adhering to the policies of the college.
• treating all participants with tolerance and respect.
• acting responsibly and reliably in administering course activities
• establishing policies and procedures that help you learn in this format
• replying to emails or phone calls within 24 hours between 9am on Monday morning until noon
on Friday afternoon.
TECHNICAL POLICES RELATED TO THE ONLINE FORMAT:
File Format Requirements: All text documents must be submitted as directed in Microsoft Word, .html,
or .pdf format, (.doc, .rtf, .html or .pdf files). Often, I will give comments to you using Microsoft Word’s
comment feature; you will need to access Word, OpenOffice, OR Google Docs to see my
comments. Other files may require other formats; look for details in the guidelines for each
assignment.
Technical Assistance: Computer difficulties are not an excuse for non-participation. If you
experience problems with Blackboard or your computer, call (608)246-6666, or toll-free at (866) 277-
4445. They can talk you through fixing many, many problems. Their hours are 7:00 a.m. to 10:00 p.m.,
Monday-Friday and 7:30 a.m. to 3:00 p.m. on Saturdays.
Problems with your personal computer (or help with webcams and the like) may be fixed if you take
your computer to Wolfpack Techies, a FREE computer repair service at Madison College for students
and faculty. Fall semester hours are Mondays and Wednesdays 12:30-5pm, Fridays 8am-5pm, and
Saturdays 8am-3pm in Truax 358.
Keep in mind that your instructor can be of only limited help in computer troubles. Your best bet is to
phone the professionals above.
Blackboard Outages: Madison College does its best to keep our Blackboard classroom up and
running. However, despite our best efforts, our virtual classroom may go down unexpectedly. It's also
possible your computer will contract a virus or worm that will make you wail and gnash your teeth.
Should this happen to you, do not panic! Phone the computer help desk at 608)246-6666, or toll-free
at (866) 277-4445. If an assignment is due, please attach it to an email to your instructor.
GRADING POLICIES:
Grading Scale: This course is graded on a credit/no credit basis. You need to earn at least 75% of the
possible points to pass the course and earn re-certification credit. Any missing assignments are
graded as a zero, not an F. You must complete all major assignments to earn credit for the class.
Preparing to Teach Online 4
5. Accessing Your Grades/Credit: I use the Blackboard Grade book to record your completed work
and credit earned; this grade book is updated weekly. To view your grades and progress in the class:
1. Select the main menu link “My Grades.”
2. Locate the “Running Total” column in the course to see your grade status. That column is the
cumulative total of all graded assignments; it will indicate if you are earning “Credit” or “No
Credit.”
If you see a hyphen (-) or a ! mark in any column, it indicates I have not yet graded your work.
Discussion Grading: Although I will track your discussion throughout the course, I will not grade each
discussion board post individually. Instead, I will assess your overall discussion at the end of our course
on the following four criteria:
1. Timeliness (overall, did you consistently meet the weekly deadlines for discussion? Did you
respond to others in a timely fashion throughout the week or wait until the very last day to post
or respond in any way?)
2. Responsiveness (overall, did you respond thoughtfully and consistently to posts of others--or
did you simply post and fail to follow-up on any of your classmate's posts?)
3. Relevance (overall, did your postings address the issues presented in the reading or other
material?)
4. Depth and Breadth (overall, did your postings suggest ways in which the topics are
complicated? Did you bring another perspective to the discussion?)
Late Work: In this course you may turn in most assignments one week late (if you need to) for full
credit. Late work will be graded late, sometimes not for several weeks, and will probably receive far
less feedback than work submitted on time.
However, group discussion will not earn any credit if completed late. All work for this course, including
final projects, needs to be turned in before August 6th at 11:59pm.
Incompletes: Because of a changing schedule from semester to semester, I cannot grant
incompletes in this class unless circumstances beyond your control arise after you have completed at
least 75% of the course. You are ineligible for an incomplete if you have not been participating in the
class or are failing.
Grading Errors: I am human; I may make an error in grading your work, particularly in this format. If
you see a zero and you did turn in the work within a week of the deadline, simply contact me for an
inquiry into the problem. Sometimes I simply misunderstand what requirement the assignment fulfills,
or where you submitted the assignment. Please contact me if I made an error.
Grading Disputes: If you feel a grade you received on an assignment is unjustified or you wish to
dispute a grade, you will need to talk to your instructor over the phone or visit her in person. I do not
respond to grade disputes via email--but feel free to email me to request a time for a phone meeting
or a time to stop by my office to discuss the situation. I am very happy to discuss your grade verbally
with you, but I think it’s best to be able to ask questions and respond in real time.
Below is a graphic representation of the course organization and content by week:
Preparing to Teach Online 5
6. Syllabus Changes: As your instructor, I retain the right to make changes based on the timeline of the
class, feedback from learners and/or logistical issues and will inform you as soon as a change is
made.
Preparing to Teach Online 6