5. The worked-out principle
Preferred by learners
Leads to superior learning
outcomes
Deep understanding
(if implemented according to specific guidelines)
8. Guidelines for example design
Self-Explanation Guideline
Help Guideline
The easy-mapping guideline
The structure-emphasizing guideline
The meaningful building-blocks guideline
9. Mark:
As we learned in our study of the split-attention principle, learners often
experience diminished results often due to the overwhelming cognitive load
created when requiring learners to integrate unintelligible visual and text
materials in multimedia instruction. According to Tarmizi and Sweller (1988),
"productive self-explanations were hindered". Given our growing
understanding of the cognitive architecture and cognitive load theory, it stands
to reason that making explanations easier through very relevant, integrated
representations will reduce cognitive load, thereby allowing for greater learning
to occur. I found it interesting that dual modality re-emerged as another factor
to increase learning within the easy-mapping guidelines, though Jeung,
Chandler and Sweller (1997) qualified earlier research by Mousavi, Low and
Sweller (1995), identifying that aural explanations of visually complex,
unfamiliar material had diminishing returns. Finally, the complexity of managing
all of the principles within the scope of the easy-mapping guideline is
punctuated with the statement "there is no definitive empirical answer to this
question" [of when to use dual modality or signalling].
10. Marcia:
According to Renkle (2005), the deep understanding achieved
from a worked-out example is seen “only if the example-based
learning is well-designed” (p. 234). Well-designed implies
many things, but I want to focus on the meaningful building
blocks guidelines. When individuals are solving problems, the
worked out examples can highlight the various “subgoals”
through signaling. This allows learners to solve new problems
and think of the individual parts of the worked-out example as
separate, not necessarily a process that must be done all
together. The studies of Catrambone (1995, 1996, 1998), have
shown that the highlighting of subgoals leads to learning and
self-explanations that create better understanding of the
individual steps.
13. Implications of the research for cognitive theory on
Learning and Instruction
Problem solving & learning are not
always two sides of a coin.
Emphasizing the importance of guided
constructive activity.
Cognitive load is an important aspect to
be considered in learning.
14. Limitations
Focusing on only one solution
No exploitation of error-trigged learning
Relevant only to a limited range of
domains
Evidence primarily from experimental
settings of limited ecological validity
15. Focusing on only one solution
Nola: One of the limitations of learning from worked-examples is the Focusing on Only One
Solution restriction which is as stated by Renkl (2005) that "traditional worked out examples show
just one solution procedure although in many cases multiple solutions are possible."
Math Problem
7x7?
7x2= 14 (2 sevens)
+14 (2 sevens)
______
28
+14 (2 sevens)
______
42
+ 7 (1 seven)
______ = 7 sevens
49
answer: 7x7 =49
16. Limitations
Focusing on only one solution
No exploitation of error-trigged learning
Relevant only to a limited range of
domains
Evidence primarily from experimental
settings of limited ecological validity
17. No exploitation of error-trigged learning
Chunhua: VanLehn (1999) emphasize that errors are
triggers for reflection that deepen understanding. For many
situations in our training meeting, we use some errors to
enhance the outcomes of learning as well. For example, we
presented some examples to show the certain function of
our service, usually, for comparing the correct examples, we
would show the audience one or two faulty solutions to
deepen their impression. I think that the faulty examples that
did not be used in the design of mutlimedia learning should
be deficit and we surely can pay more attention on it.
18. Limitations
Focusing on only one solution
No exploitation of error-trigged learning
Relevant only to a limited range of
domains
Evidence primarily from experimental
settings of limited ecological validity
19. Relevant only to a limited range of
domains
Elif: Worked-out examples include both the solution
and steps toward reaching the solution. But, solution
steps can only be provided in a limited number of
domains such as mathematics, physics, computer
programming, etc. Fortunately, recent studies have
shown that this worked-out problems can be used in
nonalgorithmic domains. Altough this restriction is
remarkable, al least the researchers started to extend
the range of domains that worked-out examples can
be used.
20. Relevant only to a limited range of
domains
Jingwei: Work-out example learning is skill-approach learning method. Hence,
the most effective domain fall into the skill based algorithms subjects. Even
though the domain range is getting broaden, the mature example-based
learning still in the algorithms domain. Since the worked-out example "consist
of a problem formulation, solution steps and the final solution." (Renkl, 2003).
The components are more suitable for the algorithms while social studies or
arts do not have certain logical procedure. If we google "how to write a good
research paper", we may have a list of how to do this which including a good
literature review, a good methodology. But they are not that accuracy to reach
the final solution - to write a really good paper. And also the standard of "a
good paper" may vary. Hence, the restriction is obvious and can not be solved
only for broaden the domain range, but also to standardlize the procedure of
the domain which need to use example-based learning method.
21. Limitations
Focusing on only one solution
No exploitation of error-trigged learning
Relevant only to a limited range of
domains
Evidence primarily from experimental
settings of limited ecological validity
22. Rachel: The potential of worked examples is very high for learning,
however, the circumstances must be right. One thing that can hinder
the circumstances are if the examples are processed superficially. This
occurs when the learner does not construct “knowledge structures” that
are relevant to the domain. This can happen due to two reasons: the
learner has processing deficiencies with the content or the worked-
example’s characteristics are suboptimal. The “suboptimal” examples
can occur if they cause extraneous load or fail to “invite” generative
processing.
I will focus on the former limitation, learner deficiencies. One thing that
can contribute to a learner having “suboptimal processing” is due to a
lack of prior knowledge. Berfthold and Renkl (2009) write that to
overcome this, it “makes sense to help out by providing instructional
explanations.” Getting everyone’s prior knowledge on the same
“playing field” seems to be one of the keys to avoiding suboptimal
processing.
25. Research-based principles for collaboration
7 issues related to CSCL systems:
Nature of technology used
Nature of the group composition
Nature of the task engaging learners
Role of students and instructors
Process of community buildings
Nature of assessments
Scaffolding collaboration
26. The Nature of technology used
Online communication
tools
Student outcomes
Web-based
communication
27. The Nature of the group composition
Gender
Group size
Learners characteristic
28. Mark: There appear to be some conflicting research findings with
regard to online gender numbers, with Bisciaglia and Monk-Turner
(2001) indicating female majority participation, versus Orly et al (2001)
who concluded the opposite. Setting aside the matter of accuracy in
determining gender participation, it would appear one of the key
differences would be females engendered a sense of community more
than their male counterparts. "Additionally, female students exhibited a
mostly connected communication pattern whie the communication of
males was mostly independent" (Rovai, 2001). Drawing upon the
asynchronous course I am taking, (and recognizing that the sample and
group data I use by no means constitutes a scientific study), this would
hold up. There is more connectedness and community amongst the
females in the group than exhibited by the males. The sense of
obligation to interact and contribute also seems diminished among the
males in the group. Outside of the gender factor, it's interesting that the
learning characteristic factors also mention females as performing
higher than low-learning oriented students (and by omission, males).
29. Jingwei: The key factor of online learning is collaboration. To
build an effective online learning, one research has drew an
attention to how demographic chracteristics affect CSCL. The
research (Tung 2010) result showed that female has higher
perceptions than male, native language speaking students are
more engaged into the CSCL, and instructors had statistically
significant higher perceptions towards online course than
students in collaboration. Female is more willing to participant
in the online discussion and share their opinion, and small
group size can envolve most students into the discusstion and
course project. The learner characteristic I think is the most
crucial factor, since it control the nature of how students
perform in online collaboration. More engagement more
effective learning outcomes can be established.
30. The Nature of the group composition
Gender
Group size
Learners characteristic
31. Marcia: “CSCL is based, not surprisingly, on the idea that
knowledge is socially constructed within a community. One
aspect of group composition is group size. Interesting, though,
that Jonassen et al (2005) do not really discuss group size in
very specific manner, instead focusing on the studies that
show that working in groups often leads to better performance
(Jessup, Egbert, & Connolly, 1995; Uribe, Klein, & Sullivan,
2003). While the best group size most likely depends on the
context (Scanlon et al., 1997), it would be interesting to
discover an upper limit to group size. This could be useful
information for MOOCs so that students could be divided into
groups that are not overwhelming. Considering that in the
Jonassen (2005) study, groups that interacted the most "felt
more interrupted and more hurried" (p. 253), having a group
with many members all trying to interact could be
counterproductive”.
32. Chunhua: For online collaborative learning environments, the
group size should be considered more carefully.
As Uribe, Klein, and Sullivan (2003) investigated, the participants
who worked in computer-mediated collaboration on solving ill-
defined problems benefited and indicated a preference for
working collaboratively. This confirmed, for certain circumstance
or task, that the participants who worked in group performed
better than participants who worked alone. Moreover, Scanlon et
al. (1997) reported that when group size rose above four that
group performance diminished for participants using an audio and
video synchronous collaboration tool. That means the design of
group size need to depend on technology as well, and I believe
that more studies and practice about this point is needed along
with the emerging new technology.
33. The Nature of the group composition
Gender
Group size
Learners characteristic
34. Nola: Learner characteristics influencing "online collaborative learning
environments provide new opportunities to compare different and more
varied groups and these these differences may contribute to the richness
and interactivity of the learning (Jonassen, Lee, Yang & Laffey, 2005)."
For example, in an online statistics course an instructor might give a survey
the first week of class asking the students how comfortable they are with
their knowledge of statistics. The levels would range from 'very
comfortable', 'somewhat comfortable' to 'not very comfortable'. Then the
instructor would divide the groups into 4 per group with varying levels of
comfort with statistics within each group. The students would use on online
discussion board to collaborate on statistic problems. As stated above "
these differences may contribute to the richness and interactivity of
learning". Those with a higher level of comfort would be able to assist
those with lower levels of comfort with statistics. Those with lower levels of
comfort may have more questions about the statistics problems. This
would lead to more interactivity between the group members as they
discuss the material.
35. Elif: In chapter 16, besides gender and group size,
learner social, cognitive, and cultural
characteristics have been investigated to explain
how they influence group activity and online
learning. Kirkley et al. (1998) found that "in higher
education online course U.S student sent more
messages than Asian students". Oppositely,
Pilkington and Walker (2003) reported that in a
virtual learning environment, "non-native speakers
make more use of the communication tools than
native students". A few factors may cause this
conflict in research: expertise level of students or
their culture.
36. Rachel: There wasn’t as much focus on gender, group size, and learner characteristic in
my chapter that I think relates to your chapters. This chapter was all about group
collaboration and what is important characteristics to ensure the collaboration is
effective and appropriate. Kirschner, Kirchner and Janssen write of three things that
make collobortion in multimedia learning effective: “1. Learning task is cognitively
demanding enough to require collaboration…” “2. Cognitive processes and information
necessary for learning are effectively and efficiently shared among group members; and
3. [the] multimedia environment provides the necessary tools for effective need efficient
communication about the task, content… and regulation of [the] processes involved in
carrying out the tasks.”
I will discuss the first necessity in effective collaboration, the learning task is cognitively
demanding enough to require collaboration. In 2010, Rajaram and Pereir-Pasarin did a
study on memory and collaboration. One would assume that memory-oriented tasks are
not “cognitively demanding” and the results showed that those that studied the lists
individually did better than those that discussed and collaborating about the lists.
However, another study was conducted by Laughlin, Bonner, and Miner in 2002. The
task was more demanding, problem solving, and the results were the opposite of the
previous study. This suggests that the difficulty of the task plays an important role.
37. The Nature of the task engaging learners
Case studies
Debates
Problem solving
38. The Role of tutors
What are the
characteristics of a good
tutor?
39. The Role of tutors
Knowledge of instructional design
Planning skills
Content knowledge
Enthusiasm and expertise
40. The Process of community buildings
Social interaction
Learning and
community
41. The Nature of the learning and communication
assessment
Essays
Concept mapping
Examinations
