ePortfolio from Successful Teaching Online Mentoring Program (STOMP), Harper College

1. STOMP ePortfolio
Alianna J. Maren, Ph.D.
Adjunct Faculty, Dept. Chemistry
Harper College
Dec. 14, 2015

2. Contents
 Community-Building Activity
 Time Management Tip List
 Final Project:
• Lesson Plan
• Assessment/Rubric developed using
Backwards Design Principles
 Final Reflections / Lessons Learned

3. Community-Building Activity (1)
Share an asynchonous community-building idea on the Week 2
discussion board (Discussion board link below.) Through reviewing
the resources above, please come up with one community-
building activity that can be implemented in an asynchronous
online learning environment. This activity can be an icebreaker, but
it can also be an activity that makes sense later in the semester
when relationships have already begun to form. When sharing
your idea, please include the following information:
Title
Task
Objective(s)
Instructions
How this idea builds community
Instructions for This Task

4. Community-Building Activity (2)
Title: Case-Study-Focused: A Community-
Building Strategy for High-Tech Classes
Task: Team builds on a group Case Study
established by the previous Cohorts
(classes). Alternatively, individuals can
pursue their own Case Study 2 options.

5. Community-Building Activity (3)
Objective(s): Apply the protocols and methods learned in
this class to an ongoing and evolving Case Study (Case Study
1) OR to a Case Study of their own choice.
 Case Study 1 Team:
 Begin using the same starting data as previous Cohorts
(and add to this database), and the same initial methods.
 They will likely have more conclusions and actual
"predictions," because they will be able to build on an
established body of work and go further.
 Considered furthering an exploratory effort.
 Case Study 2 Individuals:
 Must define their own task, collect their own task-
specific data, but will apply same or similar methodology
 Results will be unknown – another exploratory effort

6. Community-Building Activity (4)
How this builds community:
Each Cohort (class) – learns from results produced by others.
 Case Study 1 Team:
 Forms a strong working team - close to an industry-
equivalent "Tiger Team."
Reach out to others who have shown strong skills, ask
for inputs that draw from the others' unique skill sets.
Interested in applicability of others' technical results.
Case Study 2 Individuals:
 Likewise interested in the results of the Case Study 1
folks.
 Motivated to gain validation for their work by sharing
results and getting feedback & acclamation.

7. Time Management Tip List (1)
 Read through time management strategies for online
instructors from the University of Wisconsin-Stout.
 Create your own time management tip list for your
professional use, focusing on the tips that will be most
important to you. Feel free to copy and paste directly from
the webpage, and add your own notes as well. This
assignment should be incorporated into your journal
submission for this week.
Instructions for This Task

8. Time Management Tip List (2)
Selected Focus:
Getting Maximal Benefit from Synch Sessions
In previous online classes I have not used synch
sessions. One of the greatest “shifts” that I’ve had
during STOMP was learning the value of synch
sessions. My Time Management focuses on synch
sessions value to improve class cohesion; and as
being worth the investment of time.
Formal response to TWO questions raised:
1) Pros and cons - of synchronous learning as you
see it.
2) Utility - When does it make sense to utilize
synchronous online learning opportunities?

9. Time Management Tip List (3)
Responses:
1. Pros & Cons
 Pros associated with synchronous learning :
• Helps with a feeling of connection,
• Helps the teacher get a sense of how people are
responding/interacting with material, and
• Gives a different MODALITY of interaction - which suits
some learners more.
 Cons:
• Essentially the same as with f2f - timing may be
awkward for some.
 Summary Perspective: Synch learning sessions provide a
viable way to enrich the course by offering MULTIPLE
MODALITIES by which students can engage with the
content, with each other, and with the teacher.

10. Time Management Tip List (4)
Time Management for Synch Session
Usage:
2. When Does It Make Sense?
 Periodically - every few weeks or so.
This is an extra technology, and with the
plethora of learning/teaching methods
available students need to master one at a
time, and integrate it in.

11. Final Project (1)
Course: Text Analytics (an advanced data analytics
technology, garnering significant attention).
Final Project Components:
Select relevant learning objectives that fulfill the
student outcome(s) of an existing course
Create an assessment, rubric and lesson idea that
align with those objectives.

12. Final Project (2)
Relevant Student Outcomes/ Course:
 Extract both entities and concepts:
 Be able to identify, characterize, and use methods for entity and concept
co-resolution;
 Identify and characterize strategies for complex concept extraction,
 Understand the challenges with named entity co-resolution,
 Understand role of clustering and classification algorithms,
 Understand how statistical data processing maps entities and
concepts to each other,
Understand and be able to develop both ontologies and
taxonomies,
Understand the full extent and complexity of text analytics in
the context of two different Case Studies

13. Final Project (3)
Specific Learning Objectives for This Lesson:
 Understand the process overview for text analytics as
identified in Figure 4.1 in the accompanying Chapter 4 taken from
Making Sense: Extracting Meaning from Text.
 Know the various mathematical notations and formalisms, as
well as the naming conventions, used throughout this course, and
be able to apply them in your work.
 Walk through the text analytics process for your selected Data
Source Item (DSI), providing first-pass instances of the following:
Extracted Term Vector (T),
Reference Term Vector (R) – based on your DSI only,
Ontology (ontologies) capturing significant elements of your DSI; identify
which ontology nodes are essential to modeling core content. (Note:
concepts will match 1-to-1 with ontology nodes).

14. Final Project (4a)
Assessment:
Using the DSI that you have selected for work in this course,
perform the following Case Study 1 tasks, which are a form of
exploratory exercises. Later work, involving Case Study 2, will
comprise summative exercises.
 C.1.1: Using an open source term and entity extraction tool
such as FiveFilters (http://fivefilters.org/) or TerMine, input your
DSI and obtain the extracted terms.
 Associated Discussion: Reflect on this in the accompanying
Discussion 2.D.C.1.1.

15. Final Project (4b)
Assessment (Continued):
 C.1.2: Create rudimentary heuristics based on the analytic
information (term frequency, or term rank/score), identify those
terms that you would nominate for a Reference Term Vector (R).
 Associated Discussion: Reflect on this in the accompanying
Discussion 2.D.C.1.2
 C.1.3: Using your vector R as your guide, construct a
rudimentary ontology that captures essential elements in your
DSI.
Associated Discussion: Reflect on this in the accompanying
Discussion 2.D.C.1.3

16. Final Project (4b)
Assessment (Continued):
 C.1.4: Examine the DSIs posted both by this Cohort together
with DSIs posted by the previous Cohorts, select TWO that you
think would show up in a cluster with your DSI if clustering were
performed on the DSI set. What terms in your DSI, and terms in
the other two DSIs, do you think would dominate cluster
formation grouping these DSIs together?
 Associated Discussion: Reflect on this in the accompanying
Discussion 2.D.C.1.4
 C.1.5: Using a free online sentiment analysis of your choice,
perform sentiment analysis on YOUR DSI alone, and then on the
set of three DSIs – yours plus the two that you think would cluster
with yours. Is there a shift in sentiment when your DSI is part of a
cluster?
 Associated Discussion: Reflect on this in the accompanying
Discussion 2.D.C.1.5

17. Final Project (5a)
Rubric:
Assignments Unsatisfactory (0-1 pt) Competent (2 pts) Proficient (4 pts) Exemplary (6 pts)
Purpose / Alignment
with Assignment
Intention
Incomplete submission
of assignment.
Inaccurate or
inappropriate work.
Assignment
completed, but with
minimal attention to
overall goal.
Work evidences
understanding of
processes,
protocols/methods, and
data characteristics.
Work evidences deep
understanding of
assignment in the
context of goal of
developing text analytics
mastery.
Work Content Content is incomplete or
missing entirely, or
shows lack of
understanding of
processes and
protocols/methods.
Work shows basic
understanding of
concepts, processes,
and methods.
Student explores multiple
options/ alternatives for
data processing, and does
contrast/compare of
differing approaches.
Student shows insight in
data analysis, poses likely
rationales for decisions
and interpretations, and
integrates results into a
meaningful whole.
Work is exceptional and
demonstrates full
understanding of
processes/methods, plus
implications of human
decisions and impacts of
data vagaries. Work is
brought together to
include assessment of
human engineering and
data vagaries, so that an
outside evaluator can
understand impact and
ramifications of choices.
Organization /
Presentation
Work is presented in a
disorganized or non-
cohesive manner.
Content organization
is difficult to
understand/follow.
Messy or incomplete.
Work is well-organized;
easy to understand and
correlate results.
Beautiful, “showcase”
organization and
content presentation.

18. Final Project (5b)
Rubric (Continued):
Assignments Unsatisfactory (0-1 pt) Competent (2 pts) Proficient (4 pts) Exemplary (6 pts)
Reach / Integration Student attempts only
to fulfill the most
limited sense of
assignment; no sense of
creating greater
awareness of overall
process.
Student shows some
understanding of
processes. Student
decisions (“human
engineering”
component) are not
always well-
considered. Likely to
have difficulty in
applying processes/ to
other tasks.
Student shows
understanding of
processes. Student
decisions (“human
engineering”
component) are logical
and justifiable. Likely
to be able to apply
processes/methods to
other tasks.
Student demonstrates
how the work done for
assignments builds to
comprehensive
knowledge/
understanding of the
field; demonstrates
strong ability to apply
processes to other
tasks.
Effort Work is unsatisfactory;
little evidence of effort.
Work is complete, but
not brought together into
a coherent, meaning-ful
“whole.” Lack of
interpretation of results.
Lack of understanding
of how certain results
were achieved, and the
implications.
Work is complete, and is
usefully brought
together in a meaningful
way. Student places
work in the context of
overall goal. However,
work could be extended
to have more breadth
and scope.
Work exceeds all
expectations, is fully
worthy of being used to
illustrate approach to
other students and
faculty; suitable for
inclusion in the Cohort’s
Case Study.

19. Final Reflections / Lessons Learned
 Transition to online learning takes substantial
preparation time from educator
• Special attention to course formatting,
detailed instructions
• High value from well-done videos, which
take time to design and produce
 High value from synch sessions – build rapport
and community
 Educator needs to find ways to address “loss
of boundaries” with time/space blurring in
response to student needs.