How Low Can You Go? Simplifying Your Productivity Tools


RoundIcons-Free-Set-42I recently read a blog post about bad productivity habits, and one of the bad habits was using too many tools.  This really resonated with me, because in the last couple of years I’ve found myself paring down the number of tools that I use and simplifying the way that I use them.  I had realized that using so many tools meant that I was forcing myself to multitask and that I wasn’t keeping up with the things that mattered the most to me. So here’s my list of apps I use daily for productivity.

To-dos: Asana

Reference and notetaking: Evernote

Reading: This one is more complex, because I do a few different types of reading.

For news and blogs, I use Feedly

For longform reading, I either use GoodReader for pdfs of journal article, Kindle for ebooks, or books when I can’t get a book in digital form.


Precis: Non-task Sociability in CSCL (Abedin, Daneshgar & D’Ambra, 2011)


This is an installment in a series of summaries of journal articles that I have been reading.

Abedin, B., Daneshgar, F., & D’Ambra, J. (2011). Enhancing non-task sociability of asynchronous CSCL environments. Computers & Education, 57, 2535–2547. doi:10.1016/j.compedu.2011.06.002


CC Image courtesy of Sculpt

Social interactions, which enhance learning in computer-supported collaborative learning (CSCL) environments, involve both on-task and non-task (McNeil, Robin, & Miller, 2000) types of interactions.  On-task refers to pedagogical activities, and non-task refers to non-pedagogical activities like providing social support and friendship. Past literature found that non-task interaction does not occur automatically in CSCL environments.  The purpose of this study was to identify and validate the factors that influence non-task interaction. The authors created a conceptual model in which they hypothesized that control factors would affect the learners’ sense of community and the individuals’ communicative behavior adaptability.  They also hypothesized that community and adaptability would positively affect non-pedagogical sociability

The sample consisted of students from a postgraduate management degree at an Australian university.  The pilot study involved 200 student from the degree program, and the second study consisted of 210 students.  The students completed a questionnaire 13 non-task sociability items, 12 sense of community items, 15 communicative behavior adaptability items, 13 control factor items, and demographic information..

The authors used exploratory factor analysis (EFA) and found that perceptions of compatibility and self-representation were positively related to a sense of cohesion and awareness of others.  Cohesion and awareness were positively related to non-pedagogical sociability.

The study contributed to the literature by identifying five indicators of non-task sociability: finding help, sense of appealing, sense of boringness, sense of interactivity, and sense of frustration.  This student also contributes to the literature by establishing and validating a model of the factors that influence non-task sociability. The study also validated an instrument for measuring the factors in the model.

The perception of sociability factor includes social experience and relative advantage. The postgraduate students in the sample may be more experienced in social situations, therefore the lack of a relationship between learner characteristics and perception of compatibility may have been unique to this sample.  This student should be replicated with undergraduate students to determine whether learner characteristics are not an influential factor in the model.

This study serves as a framework for future research, and it leads to several other research questions.  How can instructors influence these factors to encourage non-task sociability? What level of non-sociability enhances learning?  Is there a level of non-task interaction that has a negative effect on learning?  How do different technologies enhance non-task sociability? Does the instructor’s participation in non-task interact affect the level of it? Do the tools students prefer to use of non-task interaction differ from on-task interaction and why?


McNeil, S. G., Robin, B. R., & Miller, R. M. (2000). Facilitating interaction, communication and collaboration in online courses. Computers & Geosciences, 26, 699–708. doi:10.1016/S0098-3004(99)00106-5

Precis: Social Presence in Online Learning (Sung & Mayer, 2012)


This is an installment in a series of summaries of journal articles that I have been reading.

Sung, E., & Mayer, R. E. (2012). Five facets of social presence in online distance education. Computers in Human Behavior, 28, 1738–1747. doi:10.1016/j.chb.2012.04.014


CC Image courtesy of Markus Spiske /

Social presence, the learner’s connectedness to others in the learning environment, has been well studied in the literature and found to influence learner achievement and satisfaction.  Despite these relatively consistent findings, the factors that comprise social presence have varied from study to study. The purpose of this study was to identify and validate the factors of social presence to serve as a framework for future research.

The sample consisted of 612 undergraduate students from 2 online universities.  The students completed an Online Social Presence Questionnaire (OSPQ) consisting of 30 items which they rated on a 5-point Likert scale.  The questionnaire items were selected from previously tested indicators of social presence and collected data on student perceptions.

The authors used exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to identify and validate the social presence factors.  They identified five factors: social respect, social sharing, open mind, social identity, and intimacy.  Then, using CFA, they found that the five factors were consistent across groups.

Perhaps the most significant contribution of this study is its definition of social presence.  Much of the research in social presence in the field of education cites a basis in social presence theory from the field of telecommunications, which suggests that media which supports more nonverbal cues will allow participants to more positively view their interactions (Short, Williams, & Christie, 1976).  In telecommunications social presence is an attribute of the medium, but education researchers have appropriated this theory and adapted its definition.  The authors’ study clear redefines social presence for the field of education as the, “degree of feeling emotionally connected to another intellectual entity through computer mediated communication” (Sung & Mayer, 2012, p. 1739).

Although the authors’ evidence provided well conceptualized and appropriately analyzed support for the identification of the social presence factors, the authors overextend their discussion by identifying design strategy recommendations based on these factors.  Their research does not provide support for these recommendations, and the authors note the need for future research in them.  Additionally the design recommendations seem to focus on instructor-student interaction and largely ignore the potential of student-student interaction as a possible way to influence or foster feelings of social presence.

This study serves as a solid framework for future research.  These factors could be explored in conjunction with relationship factors such as group cohesion and social interdependence to identify the relationship between the two.  Examining perceptions of social presence over time using these factors could help researchers understand how social presence can be strengthened regardless of instructor intervention. Finally social presence in small groups should be explored, because it may provide a way for students to more quickly feel connected to each other.


Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. London: John Wiley and Sons.