1. José Ramón Calvo-Ferrer jr.calvo@ua.es
TEACHING FOREIGN LANGUAGES TO DIGITAL NATIVES: IS TECHNOLOGY USE A PREDICTOR OF LEARNING SUCCESS AND STUDENT SATISFACTION?
José Ramón Calvo-Ferrer
@calvoblacksmith

2. BACKGROUND TO THE STUDY
‘Digital natives’ (Prensky 2001): students with advanced cognitive and learning skills, parallel information processing, multitasking, and effective communication skills in collaborative environments.
Traditional education perceived as ‘unattractive, boring, old-fashioned, disconnecting’ = school failure and dropout rates (Levin 2002; Prensky 2005).
Two key aspects:
Existence of a new generation of ‘tech-savvy’ students.
Prolonged exposure to technology results in advanced cognitive skills.
Need for structural changes in education (Tapscott 1998; Hartman 2005; Prensky 2005; Ramaley 2005; Akilli 2007; Tapscott 2009, etc)

4. BACKGROUND TO THE STUDY
‘Little critical scrutiny, undertheorised, and lack a sound empirical basis’ and `generational stereotyping’ (Bennett 2008).
‘Digital native’ debate based on economic factors (Bullen 2011).
‘Age not a defining factor’ regarding acquisition of technological skills (Akçayır et al., 2016, Jones and Cross, 2009; Rapetti and Marshall, 2010).
Immersion in a digital environment “may be the most important variable in predicting the behaviours of a digital native” (Teo, 2013)
Debate still present in education and media.

5. RESEARCH
RQ: Assess the effect of self-reported digital nativeness on non-technology- related abilities (i.e., SLA) and on satisfaction with the educational system.
Sample: 32 translation and interpreting undergrads (UA), aged 19 and 20.
Materials: The Conference Interpreter video game, to train students in the acquisition of mobile operating systems terminology in English.
Instruments:
Knowledge test on mobile operating systems vocabulary given as pre-test, post- test and delayed test (sixty-three items, α = .84)
Digital Native Assessment Scale (DNAS) questionnaire (Teo, 2013), given as a pre-test.
5-point Likert scale questions on satisfaction with the educational system.
Procedure: Access to video game for 3 consecutive days, sessions of 2 hours each, totalling 6 hours of practice.

7. EFFECT OF SELF-REPORTED DIGITAL NATIVENESS ON SHORT-TERM VOCABULARY LEARNING
Model Summaryb
Model R
R Square
Adjusted R Square
Std. Error of the Estimate
Durbin-Watson 1
,632
,399
,310
5,390
1,862
ANOVAa
Model
Sum of Squares df
Mean Square F
Sig. 1
Regression
521,466 4
130,366
4,487
,007
Residual
784,409 27
29,052
Total
1305,875 31
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients t
Sig. B
Std. Error
Beta 1
(Constant)
36,574
5,919
6,179
,000
Grow up with technology
3,311
1,123
,523
2,948
,007
Comfortable with multitasking
-4,468
1,458
-,585
-3,064
,005
Reliant on graphics for communication
-,592
1,421
-,072
-,417
,680
Thrive on instant gratifications and rewards
3,270
1,524
,348
2,145
,041

8. EFFECT OF SELF-REPORTED DIGITAL NATIVENESS ON LONG-TERM VOCABULARY LEARNING
Model Summaryb
Model R
R Square
Adjusted R Square
Std. Error of the Estimate
Durbin-Watson 1
,581
,337
,239
6,301
2,127
ANOVAa
Model
Sum of Squares df
Mean Square F
Sig. 1
Regression
545,659 4
136,415
3,436
,021
Residual
1072,060 27
39,706
Total
1617,719 31
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients t
Sig. B
Std. Error
Beta 1
(Constant)
38,154
6,920
5,514
,000
Grow up with technology
3,571
1,313
,507
2,720
,011
Comfortable with multitasking
-5,145
1,705
-,606
-3,018
,005
Reliant on graphics for communication
-,889
1,661
-,097
-,535
,597
Thrive on instant gratifications and rewards
1,593
1,782
,152
,894
,379

9. EFFECT OF SELF-REPORTED DIGITAL NATIVENESS ON STUDENTS’ VIEWS ON EDUCATION
ANOVAa
Model
Sum of Squares df
Mean Square F
Sig. 1
Regression
9,786 4
2,447
1,781
,162b
Residual
37,089 27
1,374
Total
46,875 31
a. Dependent Variable: I would like to use more technology in my classes
b. Predictors: (Constant), Thrive on instant gratifications and rewards, Grow up with technology, Reliant on graphics for communication, Comfortable with multitasking
ANOVAa
Model
Sum of Squares df
Mean Square F
Sig. 1
Regression
7,250 4
1,812
1,580
,208b
Residual
30,969 27
1,147
Total
38,219 31
a. Dependent Variable: I find the current educational system boring and disengaging
b. Predictors: (Constant), Thrive on instant gratifications and rewards, Grow up with technology, Reliant on graphics for communication, Comfortable with multitasking

10. CONCLUSIONS
Mixed results: grow up with technology and instant feedback vs. multitasking.
Different skills may have confronting effects on cognition.
It may be inaccurate to include all computer-related literacies under the umbrella of digital nativeness.
To analyse technological skills and their effects individually may help understand the cognitive processes and outcomes owing to technology use.
The results seem to challenge the notion that students’ digital nativeness make structural changes in education necessary.

11. LIMITATIONS AND FUTURE RESEARCH
Assumed correspondence between students’ perceptions of their digital self and actual skills.
Method of instruction may have magnified differences between learning outcomes.
It may be inaccurate to include all computer-related literacies under the umbrella of digital nativeness.
The nature of the game limited the number of participants.

12. José Ramón Calvo-Ferrer jr.calvo@ua.es @calvoblacksmith
QUESTIONS?
José Ramón Calvo-Ferrer
@calvoblacksmith

13. José Ramón Calvo-Ferrer jr.calvo@ua.es @calvoblacksmith
THANKS!
José Ramón Calvo-Ferrer
@calvoblacksmith