March 2019
ARTICLES
LEARNER ENGAGEMENT AND SUBJECTIVE RESPONSES TO TASKS IN AN EFL CONTEXT
Linh Phung, Chatham University, Pittsburgh, Pennsylvania, USA; Sachiko Nakamura, King Mongkut's University of Technology Thonburi, Bangkok, Thailand; & Hayo Reinders, King Mongkut's University of Technology Thonburi, Bangkok, Thailand


Linh Phung


Sachiko Nakamura


Hayo Reinders

Introduction

Much like motivation, engagement is a ubiquitous term used to describe a desirable quality in many contexts, including in the workplace, at school, and in college. Companies attempt to measure and improve employee engagement with the purpose of increasing productivity. Schools and universities administer surveys to assess student engagement. Materials writers aim to develop engaging materials. Teachers strive to design engaging classroom activities and tasks. In second/foreign language (L2) learning, learner engagement has recently attracted more attention with attempts to define, operationalize, measure, and investigate the construct. Engagement has long been conceptualized as the manifestation of motivation, which is often measured in the amount of student participation in learning activities or, in the context of a task, language production.

A recent article by Philp and Duchesne (2016) expands the conceptualization of learner engagement beyond the behavioral dimension (i.e., participation). These scholars recognize learner engagement as having multiple dimensions: behavioral, cognitive, social, and emotional. They define engagement as “a state of heightened attention and involvement, in which participation is reflected not only in the cognitive dimension, but in social, behavioral, and affective dimensions as well” (p. 3). They suggest some interdependence and overlap of these dimensions, which are also manifested differently in various contexts. Therefore, measures of engagement need to take into account all dimensions and the interaction among them.

In the context of a task, attempts have been made to measure engagement in its four dimensions through learners’ linguistic behaviors on task and their subjective responses to the task (Lambert, Philp, & Nakamura, 2017; Phung, 2017). The study reported here used somewhat similar measures on the four dimensions of engagement, which will be described in detail in a later section of this article.

Apart from the thorny issue of how to measure engagement, another important question is what factors contribute to higher learner engagement in task performance. Previous research has indicated that when learners have more control or choice over what tasks to perform, topics to discuss, or ideas to bring up, they are more engaged in performing tasks (Lambert et al., 2017; Phung, 2017). In addition, when learners find the topics or content familiar, personally relevant, and not too difficult, they are more likely to have a positive affective disposition to the task (Phung, 2017; Qui & Lo, 2017). Regarding choice as a variable, theoretically (i.e. according to Ryan and Deci’s Self Determination Theory) it is reasonable to assume that when learners are offered choice that supports their sense of control or autonomy, they will feel more intrinsically motivated and will be more engaged in performing a task. These empirical findings and theoretical reasoning provided the motivation for the present study, which compared the effects of choice (+constraint vs. -constraint) on learners' engagement and subjective responses to tasks. Below are the two research questions in the study.

RQ1: Were there differences in the levels of learners’ behavioral, cognitive, and social engagement in the -constraint and +constraint tasks?

RQ2: Were there differences in learners’ subjective responses to the -constraint and +constraint tasks?

Method

Twenty-four students enrolled at a Thai university completed two opinion-gap tasks and a questionnaire after each task. In one task, they were asked to discuss and agree on three items among given options (+constraint). In the other task, they discussed and agreed on three items among the options they themselves generated (-constraint). Specifically, working in a group of three, the learners were asked to come to an agreement on three new buildings that their university should construct to make it the number one university in the country for international students. Eight groups of three performed one task on one day and another task three weeks later. After they finished each task, they were asked to complete a questionnaire to report their subjective responses to the tasks. The questionnaire was developed by the researchers of the study based on existing questionnaires on enjoyment and anxiety and findings from prior research into affective responses to tasks. It used 23 six-point Likert-scale items (1 = strongly disagree, 6 = strongly agree) with six components: enjoyment (5 items), anxiety (4 items), freedom of expression (4 items), focus (3 items), task difficulty (3 items), and task familiarity (3 items).

All task performances were recorded and transcribed for coding. The following interactional variables were coded from the transcripts:

  • (1) the number of words per minute, (2) the number of turns per minute, and (3) the amount of time on task as measures of behavioral engagement

  • (4) the number of moves in sequences of negotiation of meaning and/or form per minute and (5) the number of self-repairs per minute as measures of cognitive engagement

  • (6) the number of overlaps and turn completions per minute and (7) the number of backchannels per minute as measures of social engagement

The average questionnaire score for each component was recorded for each learner after each task. The seven interactional variables and questionnaire scores were entered into SPSS 23 for data analysis. Descriptive statistics were generated. The data were explored to see if they met the normality assumptions. Many variables were positively skewed. Log 10 transformations were done for negotiation, self-repairs, overlaps and turn completions, and backchannels. After the transformations, they were negatively skewed, but the level of skewness is less serious. MANOVAs were conducted on the seven interactional variables and six questionnaire scores in the two conditions (-/+constraint).

Results

Data analyses (MANOVA and univariate tests) showed that learners generated statistically more turns, more negotiation of meaning, and more self-repairs in the -constraint task, which indicated a higher level of behavioral and cognitive engagement. Table 1 shows the descriptive statistics for the seven interactional variables. The asterisk (*) indicates statistically significant differences.

Table 1. Descriptive Statistics for the Seven Interactional Variables

Variables

Mean

Std. Deviation

-Constraint

+Constraint

-Constraint

+Constraint

Time

5.738

6.188

1.631

1.156

Words

28.932

30.746

14.782

15.706

Turns

2.804*

2.149*

1.653

1.151

Negotiation

.754*

.243*

.608

.398

Self-Repairs

1.288*

.630*

1.108

.678

Overlaps

.801

.402

.576

.416

Backchannels

.871

.618

1.233

.857

 

In other words, in the -constraint task, learners were more interactive (with more turns), made more conversation moves to clarify meaning and negotiate form, and paid more attention to or struggled more with language through self-repairs. These results suggested that when learners were less constrained in what they could bring to the group discussion, they showed more engagement in language use on task.

Regarding subjective responses, learners reported statistically significantly higher levels of enjoyment, focus, freedom of expression and, interestingly, task anxiety with the -constraint task. There were no statistical differences in the other two subjective components: task familiarity and task difficulty. Table 2 displays descriptive statistics for the six subjective components of the questionnaire with the asterisk (*) indicating statistical significance.

Table 2. Descriptive Statistics for the Six Subjective Components

Component

Task

Mean

SD

Enjoyment

-Constraint

4.642*

.741

+Constraint

4.174*

.456

Focus

-Constraint

4.903*

.777

+Constraint

4.171*

.506

Freedom of Expression

-Constraint

4.573*

.697

+Constraint

4.171*

.506

Task Difficulty

-Constraint

3.052

1.071

+Constraint

2.917

.820

Task Familiarity

-Constraint

4.167

.761

+Constraint

4.167

.702

Task Anxiety

-Constraint

4.174*

.456

+Constraint

3.083*

1.026

 

Discussions and Conclusion

The study indicates a positive effect of choice on certain aspects of learners’ behavioral and cognitive engagement, and subjective responses to tasks, a finding consistent with Lambert et al. (2017). It has been acknowledged in the educational psychology literature that choice does not necessarily result in positive outcomes, but choice that supports the needs for autonomy, competence, and relatedness usually does (Katz & Assor, 2006). Choice in this study was operationalized as the ability to bring ideas to the discussion instead of discussing ideas that were given to the learners. With this choice, learners reported that they could more freely express their ideas, focused more, and enjoyed the task more. We argue that this choice supported learners’ autonomy-related need. At the same time, the learners in this study, when given more choice, also reported feeling more anxious although they did not find the -constraint task more difficult or less familiar than the +constraint task. This indicates that anxiety in this case did not necessarily negatively affect learners’ engagement and other subjective responses (i.e., enjoyment, focus, and freedom and expression). This might be due to the fact that the two tasks were designed with a topic deemed not too difficult or unfamiliar to the learners.

We concluded that to design tasks that encourage positive responses and engagement in language use, it is favorable to give learners choice in bringing their own ideas to a discussion or solve a problem in a way that supports their sense of autonomy. In addition, some anxiety might not deleteriously affect learners’ productive linguistic behaviors and engagement. The positive findings in the study are encouraging in that these communication tasks resulted in the kind of L2 use that indicated engagement and enjoyment. Theoretically, the results of the study show the multidimensionality of learner engagement and that both learners’ behaviors and subjective responses need to be taken into account in studying learner engagement.

References

Katz, I., & Assor, A. (2006). When choice motivates and when it does not. Educational Psychology Review, 19, 429-442.

Lambert, G., Philp, J., & Nakamura, S. (2017). Learner-generated content and engagement in second language task performance. Language Teaching Research, 21(6), 655-766.

Philp, J., & Duchesne, S. (2016). Exploring engagement in tasks in the language classroom. Annual Review of Applied Linguistics, 36, 50–72.

Phung, L. (2017). Task preference, affective response, and engagement in L2 use in a US university context. Language Teaching Research, 21(6), 751-766.

Qui, X., & Lo, Y. Y. (2017). Content familiarity, task repetition and Chinese EFL learners’ engagement in second language use. Language Teaching Research, 21(6), 681-698.


Linh Phung is director of the English Language and Pathways Programs at Chatham University. Her research interests include engagement in language learning and international students’ global learning.

Sachiko Nakamura is a doctoral candidate in Applied Linguistics at KMUTT, Thailand. Her research areas include the psychology of language learning and self-regulated learning.

Hayo Reinders is professor of applied linguistics at KMUTT, Thailand and TESOL professor at Anaheim University, USA. Hayo edits the journal Innovation in Language Learning and Teaching.